CIRP ANNALS 2026
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STC A |
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A Semi-Markov Process approach to quantify material content over multiple product lifecycles with application to a hard disk drive
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Nehika Mathur (3), Yong Han Kim, Ritbik Kumar, John W. Sutherland (1)
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STC A, 75/1/2026, P.
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Keywords: Manufacturing, Modelling, Semi-Markov approach |
Abstract : Critical materials (CMs) are used in many electronic, defense, and emerging technologies, e.g., hard disk drives (HDDs). Identifying, tracking, and quantifying potentially recoverable CM from secondary sources is necessary to plan for long-term CM supply security. A Semi-Markov Process (SMP) model is employed to temporally quantify and characterize individual material flows in HDD lifecycles. The model addresses knowledge gaps by tracking individual materials in complex products subject to different end-of-use (EoU) pathways and integrates product lifecycle ‘sojourn’ times to estimate retained material quantities. The SMP shows promise as a novel approach to characterize individual material flows across complex product lifecycles.
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Simulation-based design methodology for sustainable circular battery value chains: A comparative study of Germany and Japan
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Yusuke Kishita, Ryoji Kawamoto, Marius Hermsen, Christian Scheller, Moritz Proff, Mark Mennenga, Kerstin Schmidt, Christoph Herrmann (1), Yasushi Umeda (1)
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STC A, 75/1/2026, P.
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Keywords: Lifecycle, Simulation, Circular battery value chain |
Abstract : There is an increasing need to develop sustainable circular value chains for spent lithium-ion batteries (LiBs) in response to the diffusion of electric vehicles. This paper aims to develop a simulation-based methodology for circular battery value chains by integrating scenario analysis, a market model, and a product life-cycle model. The methodology enables dynamic simulation that accounts for temporal changes and balances LiB demand and supply. A case study of Japan and Germany indicates that combining product-as-a-service models (e.g., leasing) with life-cycle management is promising for reducing CO2 emissions over the battery life cycles during 2021-2050.
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Stakeholder-weighted causal modelling for scenario-based circularity assessment in product value chains: A case of electrical/electronic equipment
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José Hidalgo-Crespo, Andreas Riel (2), Tomohiko Sakao (1)
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STC A, 75/1/2026, P.
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Keywords: Lifecycle, Decision making, Assessment methods |
Abstract : Realising a circular economy in manufacturing requires coordination across value-chain stakeholders and understanding how local design and operational decisions affect system performance. Existing life-cycle engineering approaches rely on isolated indicators and provide limited support for modelling stakeholder interdependencies. This paper proposes a stakeholder-driven assessment method that links actionable circularity indicators to system-level life-cycle performance. The method integrates Weighted Intuitionistic Fuzzy Delphi and DEMATEL to quantify causal dependencies between stakeholder-controlled indicators and value-chain variables embedded into life-cycle sustainability formulas. A ten-year Product-as-a-Service case study shows that stakeholder weighting moderates systemic and cross-value-chain effects that are difficult to capture with conventional LCA or LCC analyses.
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AI-based worker guidance in assembly and disassembly operations using multimodal ego/exo-centric data capture and structured task knowledge
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Vivek Chavan, Jörg Krüger (1)
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STC A, 75/1/2026, P.
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Keywords: Assembly, Artificial Intelligence, Multimodal assistance |
Abstract : Assembly and disassembly processes rely on expert knowledge that is difficult to document, reuse, and transfer. This paper presents a data-centricapproach for extracting structured task knowledge from expert demonstrations using egocentric and exocentric recordings. Temporal and multimodalinformation from video and narration is jointly encoded to derive structured task representations that enable procedural documentation and contextawareworker guidance. The approach is evaluated on a real-world disassembly case study, demonstrating that video-based representations captureprocedural structure and execution context beyond static image-based methods. The results highlight the potential of egocentric video understanding forrepair, training, and circular manufacturing applications. Project website: https://indego-assistant.github.io/
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Tool-based disassembly of PEM fuel cell stacks: parameter dependent design guideline
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Dominik Goes, Sebastian Henschel, Jürgen Fleischer (1)
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STC A, 75/1/2026, P.
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Keywords: Disassembly, Tool geometry, Remanufacturing |
Abstract : Polymer-electrolyte-membrane fuel cells (PEMFCs) are considered a central technology for the utilisation of green hydrogen. Disassembling stacks can improve the recycling result for critical raw materials contained and enables further circular economy strategies such as reuse or remanufacturing for suitable components. Non-destructive separation of adhered cell components poses the key challenge. A proven process requires the use of wedge-shaped cutting tools. This paper provides a construction methodology for tool design. The outlined design rules include product-to-tool parameter relationships. The methodology is validated by applying design rules to derive a specific tool geometry based on a product variant. Non-destructive proof is provided.
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ML-supported, flexible screw disassembly framework for the remanufacturing process of complex capital goods
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Richard Blümel, Sebastian Blankemeyer, Lars Aschermann, Annika Raatz (2)
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STC A, 75/1/2026, P.
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Keywords: Remanufacturing, Disassembly, Condition uncertainty |
Abstract : Remanufacturing with efficient dismantling is important for sustainable manufacturing, but condition variability of end-of-life products complicates automated, non-destructive disassembly. Exposure to challenging environmental conditions often results in seized screw connections leading to damage and loss of high-quality fasteners. This work presents a framework for complex capital goods that combines operational data with a manually operated, piezo-actuated hand tool that generates controlled low-frequency vibrations to reduce loosening torque. A data-driven, machine learning-based process selects the optimal vibration parameters from usage data. Tests on specimens and real engines have demonstrated torque reductions of up to 20%, which decreases the need for rework.
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A vision-based approach combining event and RGB sensors towards human-robot collaborative assembly
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Qiang Qin, Sebastian Thiede (2), Ruirui Zhong, Xi Vincent Wang (2)
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STC A, 75/1/2026, P.
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Keywords: Human robot collaboration, Assembly, Event sensor |
Abstract : Human-robot collaborative assembly (HRCA) requires rapid and reliable perception of human actions to coordinate timely robotic assistance. This paper proposes a vision-based approach combining event-based human action recognition and RGB-based object pose estimation. An EventPointnet++ network is developed to recognize assembly actions from event sensors, while RGB sensing supports accurate object pose estimation. Experiments show that EventPointnet++ achieves 99.25% recognition accuracy with a latency of 2.16 milliseconds. The integrated pipeline is verified in an engine assembly case study, demonstrating improved responsiveness and fluency in HRCA.
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Foundation model-based end-to-end policy for robotic assembly
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Sichao Liu, Ethan Regal, Hanzhi Zhang, Chongnan Wang, Lihui Wang (1), Robert X. Gao (1)
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STC A, 75/1/2026, P.
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Keywords: Robot, assembly, Foundation model |
Abstract : Despite rapid advances in foundation models, achieving robust and reliable performance in complex assembly tasks remains a substantial challenge. This paper introduces a foundation model-based approach for learning end-to-end assembly policies involving both robots and humans. A unified framework built on the LeRobot platform is developed for robot teleoperation, data collection and curation, model fine-tuning, and local deployment on robotic systems. Using assembly-oriented language instructions, state-of-the-art foundation models are fine-tuned under different parameter configurations and evaluated comprehensively. Successful policy deployment with asynchronous inference and long-horizon action chunking on a partial car engine assembly demonstrates the effectiveness of the developed methods.
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Towards data-driven quality monitoring of human-centric assembly operations
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Apostolis Papavasileiou, Konstantinos Gkouvas, Dimitris Boulbasakos, Sotiris Makris (2)
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STC A, 75/1/2026, P.
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Keywords: Quality control, Artificial intelligence, Human robot collaboration |
Abstract : The increasing demand for handling product variety in manufacturing has created the need for flexible solutions in human-centric assembly operations. This paper presents a data-driven approach for quality monitoring of such operations incorporating augmented reality, wearables and cameras for operators’ performance monitoring. Force control and Artificial Intelligence (AI)-based object detection are utilized to ensure proper assembly from robot. The solution is applied as an overall architecture for quality monitoring, covering the data-driven factors affecting products’ quality under assembly operations. This is being validated under an elevators manufacturing case where an operator is collaborating with a robot for electrical cabinet’s assembly.
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A vision-language conditioned physics-aware imitation learning approach for bimanual robotic dexterous assembly
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Tian Wang, Benhua Gao, Haofei Ma, Guoquan Zhang, Duidi Wu, Pai Zheng (2)
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STC A, 75/1/2026, P.
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Keywords: Human-robot collaboration, Manufacturing system, Imitation learning |
Abstract : Increasing complexity and precision in Human–Robot Collaborative Assembly (HRCA) require robots to understand language, vision, and tactile information for contact-rich manipulation. To address the challenge, this paper proposes a vision-language conditioned physics-aware imitation learning approach for bimanual dexterous assembly. Firstly, a Mixed Reality (MR)-based bilateral teleoperation system is designed for multimodal human demo collection. Then, a Vision-Language Model (VLM)-augmented physics-aware diffusion policy is developed for manipulation skill learning. Furthermore, a coarse-to-fine visual Chain-of-Thought (CoT) strategy is integrated for task planning. Finally, the proposed method has been demonstrated on a dual-arm dexterous hand-based robotic platform by performing various HRCA tasks.
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Label-free monitoring of screw driving using anomaly detection and fault clustering
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Nikolai West, Jochen Deuse, Sami Kara (1)
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STC A, 75/1/2026, P.
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Keywords: Assembly, Quality control, Machine learning |
Abstract : Industrial screw driving quality control often relies on supervised machine learning requiring labeled fault examples for each process variant, creating costly deployment barriers. This paper presents a two-stage unsupervised framework detecting and categorizing faults without labeled training data. Stage 1 employs deliberately over-sensitive anomaly detection to maximize recall. Stage 2 applies time-series clustering with known-good reference samples: fault-pure clusters indicate real defects, while clusters co-locating with references reveal false positives for filtering. Validation on 1,457 industrial operations across 5 fault classes achieves 82.3% F1-score (96% recall, 89% precision), approaching supervised classification (86.6-88.7%) while enabling zero-label deployment and unknown fault detection across manufacturing variants.
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Process-adapted electrostatic handling for future metallic battery electrodes
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Jonas Schwieger, Do Minh Nguyen, Christian Wacker, Klaus Dröder (2)
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STC A, 75/1/2026, P.
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Keywords: Handling, Electrode, Assembly |
Abstract : Metallic foils for battery electrodes require highly developed handling techniques to avoid contaminating or damaging the substrate. Additionally, deposition accuracy and cycle times are key requirements for scalable and efficient assembly processes. Within this context, the present research investigates material-adapted electrostatic handling of metallic foils. The newly developed grippers utilize Coulomb forces, a low-frequency AC power supply and a polyethylene (PE) dielectric material, enabling high-quality handling without external media consumption. Experimental investigations demonstrate safe handling as well as fast and accurate positioning of sample battery electrodes based on lithium foils, opening up future possibilities for industrial use.
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STC C |
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Effect of process-induced anisotropy on flow stress characterization and chip formation in the machining of extrusion-based additively manufactured stainless steels
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Ali Hosseini, Mohammad Valiyan, Muhammad Asim Ghaffar, Jannis Saelzer, Sebastian Berger, Ahmad Barari, Hossam A. Kishawy (2), Dirk Biermann (1)
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STC C, 75/1/2026, P.
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Keywords: Cutting, Machining, Additive manufacturing |
Abstract : Material extrusion additive manufacturing, particularly metal fused filament fabrication (MFFF), is advancing rapidly in industry. However, MFFF parts require post-process machining to meet quality standards. The layer-by-layer nature of MFFF introduces anisotropy, which affects machining performance depending on print orientation. This paper investigates the machining characteristics of MFFF 17-4PH and 316L stainless steels. Quasi-static tensile tests, split Hopkinson pressure bar experiments, and finite element analysis were performed to determine the Johnson–Cook plasticity and damage parameters for force modeling. The results reveal a complex cutting regime for MFFF, emphasizing the fundamental differences in machining characteristics of FFF and wrought materials.
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Engineering consistent machining forces in functionally graded materials
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Xiaoliang Jin, Farshad Kazemi, Zhenghui Lu, Adam T. Clare (1), Rachid M'Saoubi (1)
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STC C, 75/1/2026, P.
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Keywords: Milling, Force, Functionally graded materials |
Abstract : Additive manufacturing enables multi-material functionally graded materials (FGMs) with expanded functionality, yet post-machining remains challenging because flow stress varies with composition. This paper presents a data-efficient, physics-guided Gaussian process (GP) model for predicting milling forces in SS316/IN718 FGMs without repeated force-coefficient identification. A physics-based milling model with mixture-law baselines is corrected using sparse force measurements, while the GP learns the residual as a smooth function of composition and parameters. The model reduces prediction error from 26.6% to 19.2% for feed force and from 19.8% to 10.6% for normal force, while adaptive feed scheduling lowers peak-force variation from ~50% to ~8%.
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Assessment of local microscale residual stresses induced by variable uncut chip thickness in turning using large-field FIB-DIC
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Gorka Ortiz-de-Zarate (3), Andrey Chuvilin, François Ducobu (2) , Aitor Madariaga, Mikel Etxebeste, Pedro J. Arrazola (1)
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STC C, 75/1/2026, P.
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Keywords: Residual Stress, Surface Integrity, Turning, FIB-DIC |
Abstract : Variable uncut chip thickness in turning induces spatially heterogeneous thermomechanical loadings that strongly affect residual stress (RS) generation. Conventional techniques, such as laboratory X-ray diffraction (XRD), provide spatially averaged RS values over millimetre-scale areas and cannot resolve local surface RS gradients. This work introduces a large-field Focused Ion Beam-Digital Image Correlation (FIB-DIC) methodology using slits and ring-cores to quantify local microscale RS, combined with stereo profilometry to correlate stresses with surface topography in turned Ti-6Al-4V ELI. The results reveal peak-to-valley RS variations up to 1000 MPa, undetectable by XRD, highlighting their potential impact on fatigue, corrosion, and surface-driven component performance.
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A Microstructure-based dynamic recrystallization model for dry machining of AISI 4140 with in-situ kinematic and thermal calibration and validation
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Julius Schoop, German Gonzales, Avery Hartley, Volker Schulze (1), I.S. Jawahir (1)
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STC C, 75/1/2026, P.
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Keywords: Surface integrity, In-process measurement, Predictive model, Finite element method (FEM). |
Abstract : A calibration methodology for physics-based dynamic recrystallization (DRX) modelling in machining is presented, based on full-field, in-situ thermal and kinematic measurements based on high-speed digital image correlation (DIC). Streamline-resolved shear strain histories obtained from DIC are used to constrain DRX activation in terms of the critical and saturation dislocation densities of a microstructure-based model. Local tool–chip interface temperatures are independently measured using three integrated thin-film thermistors The methodology is demonstrated for dry orthogonal cutting of AISI 4140, where predicted recrystallized layer depths Zgs show good agreement with focused-ion-beam (FIB) cross-section measurements. The results establish DIC-based kinematic calibration as a robust and physically grounded route for microstructure modelling.
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Machining-inducted residual lattice strain and ductile-brittle transition in sapphire revealed by X-ray nanoprobe diffraction microscopy
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Rui Liang, Tao Zhou, Rui Liu, Sangkee Min (2)
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STC C, 75/1/2026, P.
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Keywords: Ultra-precision machining, Strain, X-ray nanoprobe diffraction microscopy |
Abstract : Hard X-ray nanoprobe diffraction microscopy is employed to investigate machining-induced residual lattice strain in single-crystal sapphire following ultra-precision orthogonal plunge cutting. In this study, tilt-series and single-angle acquisition strategies are systematically compared to evaluate their capability for resolving lattice variations associated with the machining process. An analytical framework is developed to enable efficient and reliable extraction of the strain, serving as strain-based indicators of changes in the dominant deformation mechanism. The measured high-dimensional strain exhibits spatial heterogeneity and systematic evolution along the cutting path, consistent with deformation-regime changes from ductile response to crack-prone behavior.
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Milling CFRP using custom-fabricated single-crystal diamond tools
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Eren Tuncer, Mahmoud Alipour Sougavabar, Adnan Kurt, Ismail Lazoglu (1)
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STC C, 75/1/2026, P.
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Keywords: Milling, Diamond tool, Composite |
Abstract : This article evaluates the milling performance of custom-fabricated single-crystal diamond (SCD) cutting tools during machining of carbon fiber–reinforced polymer (CFRP) composites. To mitigate the high cost of commercial SCD tools, milling cutters were fabricated by brazing SCD cutting edges with radii below 300 nm. SCD tools with axial rake angles of 0°, 5°, and 10° were assessed under controlled milling conditions. Cutting forces and torques were acquired using a rotary dynamometer. The results show that SCD milling tool geometry and cutting conditions strongly governs cutting mechanics, with a neutral axial rake angle providing better performance in CFRP milling.
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Enhancement of deep-hole boring accuracy via on-machine measurement and compensation
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Pengfei Zhang, Ang Li, Wei Yang, Hanxiao Zhao, Liming Shu, Naohiko Sugita (1), Bi Zhang (1)
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STC C, 75/1/2026, P.
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Keywords: Boring, Error, On-machine measurement and compensation |
Abstract : To improve the machining accuracy of deep-hole boring, this study, for the first time, develops an on-machine measurement and error compensation system for deep-hole boring. Experimental results show that the shape errors measured by the developed on-machine device are in close agreement with those obtained using a coordinate measuring machine, with a maximum deviation of no more than 3 μm; after applying the proposed compensation strategy, the cylindricity error is reduced by up to 45.5%, and the taper error by up to 96.4%. Moreover, with the proposed method, the machining accuracy of the workpiece exhibits significantly higher repeatability and stability.
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“Chip-guide drilling” – a new high-efficiency non-stop drilling method
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Takehiro Hayasaka (2), Hikaru Akari, Katsuhisa Saito, Naoki Sumiya, Kyungki Lee, Eiji Shamoto (1)
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STC C, 75/1/2026, P.
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Keywords: Drilling, Chip, Guide grooves |
Abstract : In drilling, chip clogging stands as a major obstacle. For suppression, technologies such as pecking / high-pressure coolants are utilized. However, they have disadvantages, e.g., low efficiency / high energy consumption, respectively, and higher efficiency is required for deep holes. In this paper, a new high-efficiency non-stop drilling method is proposed by suppression of chip clogging through generation of straight/continuous chips via guide grooves. Moreover, the flute volume can be decreased because of these chips, resulting in increased drill strength; efficiency can be increased even more. Experiments against aluminum/copper alloys are conducted to verify the proposed method.
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Measurement of thermal tool loads in machining with cutting fluids
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Berend Denkena (1), Benjamin Bergmann (2), Malte Kraeft, Jan Schenzel
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STC C, 75/1/2026, P.
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Keywords: Temperature, Cutting tool, Cutting fluid |
Abstract : Knowledge of thermal tool loads is essential for the design of cutting fluid supply strategies. An in-situ thermography-based method is presented for measuring temperature distributions at 1.9 μm/pixel and 670 Hz under cutting fluid pressures up to 80 bar. The method is validated by two-color pyrometry and finite element simulations, enabling analysis of the influence of cutting fluid supply on thermal tool loads and the energy efficiency of cutting processes. The investigations show that at a pressure of 45 bar and an adapted cutting fluid nozzle diameter lead to reduced thermal loads and minimized energy consumption of the pump.
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Cutting of highly deformable soft materials: Role of material deformability and tool geometry
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Urara Satake (2), Tatsuya Suzuki, Toshiyuki Enomoto (1)
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STC C, 75/1/2026, P.
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Keywords: Cutting, Cutting tool, Soft material |
Abstract : Hydrogels have emerged as attractive functional materials owing to their softness, biocompatibility, and, more recently, toughness. In cutting processes, however, tough hydrogels undergo excessive deformation before crack initiation, causing functional degradation. This study examines cutting of tough hydrogels that require more than an order of magnitude larger deformation for crack initiation than rubber. Cutting experiments demonstrate that tough hydrogels exhibit responses distinct from conventional elastomers, while finite-element simulations reveal that these originate from extreme deformability. For highly deformable materials, cutting behavior is governed by overall tool geometry rather than tip sharpness alone, leading to geometry-based tool design strategies.
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Physics-informed machine learning towards predictive modelling and physical mechanisms decoupling of crater formation in Ti6Al4V machining
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Hongguang Liu, Shijia Shi, Xin Liu, Jun Zhang, Wanhua Zhao, Tian Huang (1), Gérard Poulachon (1)
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STC C, 75/1/2026, P.
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Keywords: Wear, Machine learning, Physics-informed neural network |
Abstract : Crater wear is a major limitation of machining efficiency and quality for difficult-to-cut Ti6Al4V alloys. In this study, a physics-informed neural networks (PINNs) model is proposed for predictive modelling of crater formation, where multiple physical laws are derived as the loss function to modulate the training process. Thermomechanical loads at the tool-chip interface are obtained by experiments and an analytical model. The proposed model shows good agreements with experimental data, which also constructs the link between the microscopic and macroscopic perspectives for understanding crater formation, as well as providing an approach for quantitative analyses of wear mechanism composition.
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Grey-box model–integrating tribology descriptor for tool wear prediction in milling
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Amirmohammad Jamali, Amod Kashyap, Finn Rümenapf, Nelson Filipe Lopes Dias, Wolfgang Tillmann, Johannes Schneider, Michael Stüber, Volker Schulze (1)
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STC C, 75/1/2026, P.
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Keywords: Tool wear, Tribology model testing, Grey-box framework, Coated cutting tools |
Abstract : Tool wear prediction in milling often relies on extensive experiments or data-driven models, limiting efficiency and interpretability. This study introduces a process–tribology descriptor linking a coating-specific tribological wear parameter from model tests to time-dependent tool wear. A coating-specific wear rate is embedded within a structured wear formulation to describe coating-dependent behavior across machining conditions. A physics-informed grey-box model further incorporates machining parameters and thermo-mechanical effects, enhancing predictive robustness. The approach preserves the relative wear ranking of coatings and enables efficient, transferable, and physically interpretable tool wear modeling within the tested machining parameter range. tool wear, tribology model testing, grey-box framework, coated cutting tools
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Tchebychev-based modal-domain coupling (TMDC) for prediction of microtool-tip dynamics
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O. Burak Ozdoganlar, Shivang Shekhar, Alec Vucsko, Kadir Kiran, Bekir Bediz / A. Donmez (1)
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STC C, 75/1/2026, P.
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Keywords: Micro machining, Dynamics, Modal-domain coupling |
Abstract : Accurate representation of tool-tip dynamics is essential for predicting stability in micromachining. Frequency-domain coupling approaches amplify measurement noise due to matrix inversions and finite-difference approximations of rotational frequency response functions (FRFs). We propose Tchebychev-based modal-domain coupling (TMDC), which represents measured spindle–artefact mode shapes in a Tchebychev basis, evaluates slopes with spectral differentiation, couples a Tchebychev-based tool-dynamics model, and enforces interface compatibility in modal coordinates. TMDC is validated on two ultra-high-speed spindles, showing agreement with measured FRFs up to 15 kHz and avoiding the artificial antiresonances observed with receptance coupling substructure analysis (RCSA). Predicted tool-tip receptances are then used to predict stability for two micro-endmill geometries.
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STC Dn |
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Method-enforcing AI for product-service system design: Conformance gains and acceptance tradeoffs in an expert evaluation
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Tatsunori Hara (2), Wuyi Chen, Jun Ota
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STC Dn, 75/1/2026, P.
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Keywords: Design, Large language model(s), Human–artificial intelligence collaboration |
Abstract : Product–service system design methodologies face adoption challenges because of their cross-domain procedural complexity. Large language model (LLM)-based agents can address this. We developed Service LAD (LLM-Agentic Design), a method-enforcing AI framework embedding methodological knowledge into autonomous tools. Using an expert workshop (N = 4) with a crossover design, we compared it with method-flexible AI for conformance and human factors. The method-enforcing approach achieved higher conformance (99% vs. 82% step compliance; 99% vs. 37% output completeness; 87% vs. 51% traceability), whereas practitioner acceptance was moderated by domain familiarity. The conformance–acceptance tradeoff is conditional, providing evidence for methodology-embedded design support.
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Nonlinear tolerancing through high fidelity variation simulation of deformable parts under frictional contact
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Roham Sadeghi Tabar, Kristina Wärmefjord, Lars Lindkvist, Rikard Söderberg (1)
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STC Dn, 75/1/2026, P.
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Keywords: Tolerancing, Friction, Quality Assurance |
Abstract : Friction at contact interface strongly influences compliant assembly variation, yet most nonrigid variation simulation tolerancing workflows still assume frictionless contact. This paper presents a novel nonlinear variation simulation and unilateral contact considering Coulomb friction solved as a second order cone program, enabling nonlinear tolerancing with practical computational cost. The method is demonstrated on an industrial assembly with perturbed geometries. Compared to a frictionless baseline, the proposed model captures stick and slip effects and yields lower tangential slip and reduced variation across defined contact zones. The results highlight the necessity of frictional contact modeling for tolerance analysis in compliant assemblies.
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From natural language to RL formulation: a digital twin–centered optimization framework for manufacturing systems
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Haolin Fan, Bingbing Li, Jiajun Ma, Edward Chow, Jery Ying Hsi Fuh, Hong-Chao Zhang (1)
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STC Dn, 75/1/2026, P.
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Keywords: Digital twin, Artificial intelligence, Autonomous manufacturing |
Abstract : Digital twins (DTs) are widely used in manufacturing for simulation-driven analysis and optimization. As optimization increasingly handles complex dynamics, constraints, and uncertainty, reinforcement learning (RL) becomes a natural choice. However, RL adoption in manufacturing remains limited due to the complexity and fragility of problem formulation. This paper presents a DT-centric optimization framework that enables practitioners to specify optimization intent at the process level while automatically generating executable RL formulations. An evolving playbook consolidates formulation knowledge across optimization cycles. Experiments show a 28% increase in final return, a 27% reduction in convergence time, and a stable success rate of 0.87.
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Grayscale digital light processing enabled generative design of material-graded disordered structures
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Ke Xu, Yubin Gao, Junjie Cao, Canhui Lin, Paul Maropoulos (1), Yingguang Li (2)
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STC Dn, 75/1/2026, P.
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Keywords: Design method, Structure, Grayscale digital light processing |
Abstract : Disordered structures offer extended design freedom and robustness for functional components. However, the geometric complexity may cause severe stress concentration. This paper presents a generative design method for Material-Graded Disordered Structures (MGDS) enabled by grayscale digital light processing (g-DLP). Unlike conventional design with homogeneous materials, this method integrates structural design with material gradient. Taking predefined stiffness distribution as design target, disordered structures are generated using Gaussian random field and further optimized with graded material distribution for g-DLP fabrication to mitigate stress concentration effect. Experiments proved effectively enhanced reliability of the designed MGDS, and its potential in much wider engineering applications.
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Generative AI-based risk assessment and hazard identification towards safety compliant workplace design
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Konstantinos Katsampiris-Salgado, Nikos Dimitropoulos, George Michalos (2)
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STC Dn, 75/1/2026, P.
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Keywords: Generative artificial intelligence, Safety, Inspection |
Abstract : This paper presents a framework for automated industrial safety assessment combining retrieval-augmented generation with multimodal large language models. The approach integrates visual scene analysis with normative standard retrieval to enable context-aware hazard identification and risk classification. A modular three-layer architecture implements dual-mode knowledge retrieval and structured inference pipelines for ISO compliance evaluation. Experimental validation on a collaborative robotic manufacturing cell demonstrated good detection performance across hazard categories, with consistent identification of regulatory violations requiring negative constraint reasoning. Results indicate effectiveness for decision-support in safety-critical manufacturing environments, reducing inspection time while maintaining alignment with expert assessments.
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Design for additive manufacturing of irregular architected structures using wave function collapse
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Nanya Li, Changkun Sun, Qiang Cheng, Yi Xiong, Stephen Chih-Yang Lu (1)
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STC Dn, 75/1/2026, P.
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Keywords: Design optimization, Additive manufacturing (AM), Wave function collapse. |
Abstract : Empowered by the meticulous engineering design of lightweight architecture, the construction of irregular architected structures has been explored to seek exceptional performance. However, the design framework of irregular parts that can be additively manufactured remains debated. In this paper, pioneering research on differentiable wave function collapse (d-WFC) has been presented to define the compatibility of 3D tiles. Fundamentally, this method tackles the challenge related to the connection rules of tiles for structure optimization and manufacturability. A novel parallel d-WFC has been adopted to generate gradient-compliant stochastic structures with high mechanical properties, while drastically increasing computing efficiency.
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Metrics-driven optimization for circular product design
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Fazleena Badurdeen, Junwon Ko, I.S. Jawahir (1)
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STC Dn, 75/1/2026, P.
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Keywords: Optimization, Lifecycle, Circular economy |
Abstract : Designing products that embody circular economy principles is central to enabling macro-economic transition away from linear production practices and mitigating their associated environmental impacts. However, circular product design (CPD) is inherently complex, requiring trade-offs among functionality, cost, and numerous product circularity-driven requirements. While comprehensive product circularity metrics enable systematic assessment of such requirements, existing CPD optimization efforts are often limited by incomplete metric integration and insufficient consideration of interdependencies and trade-offs. Moreover, optimization alone does not guarantee robust or fail-safe CPD outcomes. This paper presents a novel axiomatic design-leveraged, product circularity metrics-driven approach to address these limitations.
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Modeling correlated non-normal contributors in geometric stack-up analysis
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Mattia Maltauro, Edward Morse (2), Roberto Meneghello, Gianmaria Concheri
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STC Dn, 75/1/2026, P.
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Keywords: Design optimization, Tolerancing, Tolerance Stack-Up with covariance |
Abstract : This work presents a computational framework for tolerance chain analysis based on multivariate statistical modelling accommodating both prescribed moments and correlations. The proposed method generates multivariate datasets matching either measured or proposed component characteristics, enabling realistic statistical virtual assembly. By using a transformed multi-variate Normal distribution, it is possible to represent the mean, variance, skewness, kurtosis, and covariance structure of the real parts' geometric variability. This allows tolerance propagation analysis that reflects actual manufacturing variability. Applications include predictive assembly simulations, functional tolerance optimization, and data-driven design verification in industrial contexts.
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Generative adaptable design enabled by predictive change propagation
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Zhilin Sun, Dengzheng Chi, Kaifeng Wang, Lei Wang, Peihua Gu (1)
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STC Dn, 75/1/2026, P.
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Keywords: Design, Information, Generative adaptable design |
Abstract : Adaptable design provides a systematic method to generate candidate designs under uncertain requirements and quantitatively evaluate their adaptabilities. Considering the impact of design change propagation, this paper presents a framework for generative adaptable design, in which extra design effort is formulated as information content to evaluate design adaptability. Design change propagation is modeled using a hidden Markov model, and entropy is employed to characterize propagation uncertainty and guide the generation of adaptable design strategies. A case study on nonstandard automation equipment demonstrates that the proposed approach enables the generation of adaptable design solutions with controlled design effort.
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STC E |
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Heat input control and deep learning-based indirect measure of process and deposition stability in Wire Arc Additive Manufacturing
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Alessandra Caggiano (2), Giulio Mattera, YuMing Zhang, Roberto Teti (1)
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STC E, 75/1/2026, P.
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Keywords: Additive manufacturing, Process control, Layer deposition stability |
Abstract : A process qualification-oriented data-driven framework for Wire Arc Additive Manufacturing (WAAM) integrating qualification data, process monitoring and feedback control, is presented. A proportional control strategy regulating heat input by varying the Contact Tip–to–Workpiece Distance (CTWD) is developed to enhance process stability, ensure consistent layer geometry and maintain the qualified heat-input conditions for process qualification. To assess the control strategy stability, deep learning-based CTWD soft sensing from high-frequency welding signals is combined with an uncertainty-aware process quality index. The framework is validated on Invar 36 alloy, but it supports extension to other alloys and arc welding-based additive processes.
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Electrode wear pattern and compensation of fast electrical discharge flank milling
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Juncheng Lu, Yifan Lu, Bin Li, Xuecheng Xi, Yaou Zhang, Wansheng Zhao (2)
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STC E, 75/1/2026, P.
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Keywords: Electrical discharge machining (EDM), Electrode wear compensation, Fast electrical discharge flank milling |
Abstract : This study unveils a specific pattern of electrode wear in fast electrical discharge flank milling, which deteriorates the geometric accuracy of machined surfaces due to severe radial electrode wear. Based on a thorough understanding of the wear traits observed via a high-speed video camera, a stage-specific wear compensation strategy is proposed accordingly. It relies on machining stage identification through gap voltage analysis, combined with the integration of radial, axial, and pose compensations. By integrating it into the CNC trajectory interpolation algorithm, experiments have proven its ability to reduce dimensional error and profile error to 18.21 μm and 18.98 μm, respectively.
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Jet-electrochemical discharge turning of glass
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Genglin Zhu, Yonghua Zhao, Chunjiang Wu, Masanori Kunieda (1)
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STC E, 75/1/2026, P.
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Keywords: Electrolyte jet, Micro machining, Electrochemical discharge turning |
Abstract : The Jet Electrochemical Discharge Turning (Jet-ECDT) process is developed for micromachining non-conductive cylindrical components. An electrolyte jet was used as the tool in place of a solid tool electrode to overcome the limitations of conventional electrochemical discharge machining, such as workpiece deformation caused by solid tool-workpiece contact, and poor machining reproducibility due to an unstable gas film. This study theoretically clarifies the mechanism of discharge localization on the cylindrical workpiece. The critical process parameters were investigated to produce complex microfeatures with diameters down to 29.9 μm and to achieve a high surface quality (Sa 56 nm) on quartz micro-rods.
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Towards adaptive electrochemical machining via signal-based data-driven modelling
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Elio Tchoupe Sambou, Andreas Klink (2), Tim Herrig
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STC E, 75/1/2026, P.
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Keywords: Electro chemical machining (ECM), Digital twin, Monitoring. |
Abstract : Electrochemical machining remains largely restricted to medium- and large-batch production and to companies with substantial prior experience despite its significant potential, driven by advantages such as contact-free machining and virtually wear-free operation. This limitation arises from the strongly experience-based nature of present process setups. Reliable process monitoring is a prerequisite for the implementation of adaptive and closed-loop control. This paper demonstrates how process dynamics can be monitored using data-driven models trained on historical machining signals, enabling the inference of prevailing process conditions directly from measured data and forming a basis for future closed-loop process control.
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Digital modeling of small-hole electrical discharge machining using a local discharge frequency model incorporating discharge delay time
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Tomohiro Koyano (2)
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STC E, 75/1/2026, P.
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Keywords: Electrical discharge machining (EDM), Digital twin, Discharge delay time |
Abstract : An electrical discharge machining model for determining the local discharge frequency based on the average discharge delay time is proposed and applied to small-hole drilling simulations. The effects of tool electrode curvature and inclination on the local discharge frequency and gap distance are successfully reflected in the simulation results. By incorporating the influence of debris concentration on the discharge delay time, good agreement between simulated and experimental results of the tool and workpiece profiles is achieved. The model enables near real-time visualization of gap distance and debris concentration distributions, thereby enabling its application to digital twin implementations.
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Atomic and close-to-atomic-scale finishing of sapphire via laser-enhanced plasma vaporization machining
|
|
Peng Lyu, Jiyu Pan, Ze Liu, Yuexiang Wang, Fengzhou Fang (1)
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STC E, 75/1/2026, P.
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Keywords: Plasma, Laser, Atomic and close-to-atomic scale manufacturing (ACSM) |
Abstract : Laser-enhanced plasma vaporization machining (LEP-VM) is proposed as a hybrid process that integrates laser heating with plasma-assisted chemical reactions for hard, brittle crystalline materials. The process enables chemically driven material removal while suppressing redeposition through in-process gas flow optimization. Characterization demonstrates atomic-scale surface finishing, with a surface roughness of 0.13 nm, and damage-free subsurface integrity, without amorphization or lattice degradation. Mechanistic analysis indicates that localized laser heating activates thermally assisted, topography-selective reactions that drive the convergence of surface roughness. These findings confirm that LEP‑VM provides a promising pathway for simultaneously achieving surface smoothing and figure‑related material removal on sapphire.
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|
Generation of diamond structure by ion implantation and self-limited laser-induced atom desorption
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Jinshi Wang (2), Shan Wu, Yuetong Zhang, Yifan Tian
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STC E, 75/1/2026, P.
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Keywords: Laser micro machining, Atomic and close-to-atomic scale manufacturing, Diamond |
Abstract : Laser machining is one of the most commonly used techniques to fabricate micro and nano structures on diamond. However, it is challenging to obtain a high surface quality by traditional ablation process. In this study, a novel method is proposed based on self-limited atom desorption accomplished by pulsed laser irradiation and ion implantation. Formation of amorphous carbon induced by ion beam plays a critical role in the selective material removal, and the atomic scale mechanism enables remarkable improvements in surface integrity and controllability. Experimental results demonstrate the potential of this method in the development of advanced diamond devices.
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Precision laser microdrilling of sapphire via reducing transient pressure
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Guoqi Ren, Yusuke Ito, Masayuki Nakao (1)
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STC E, 75/1/2026, P.
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Keywords: Laser micro machining, Precision, Stress wave |
Abstract : Ultrafast lasers are used for micromachining transparent hard and brittle materials, but cracks and damage are challenges. Here, we demonstrate precision microdrilling in sapphire through temporally shaping ultrafast laser pulses. The strategy aims to suppress transient strong pressure in processing regions by minimizing direct laser absorption by materials. The shaped pulse has an initial ultrafast spike for electron excitations, followed by a flat tail having subnanosecond width for plasma heating. The plasma absorbs laser energy during its expansion and simultaneously ablates materials, weakening transient stress wave and pressure, avoiding cracks and damage. High-quality microholes are fabricated by multiple shaped pulses.
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Closed-loop laser planarization of diamond guided by white-light interferometry
|
|
Reina Yoshizaki, Yuta Teshima, Yangjin Kim, Kenichi Hibino, Yanming Zhang, Doo-Man Chun (1), Masayuki Nakao (1)
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STC E, 75/1/2026, P.
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|
Keywords: Laser beam machining (LBM), Polishing, On-machine measurement |
Abstract : Feedback-based laser processing is introduced as a fully noncontact route to closed-loop planarization and surface-quality control of diamond within the spatial bandwidth stably measurable by on-machine white-light interferometry. At each iteration, the measured topography is used to update ultrashort-pulse laser irradiation coordinates for selective protrusion removal. Dual-exposure phase fusion improves metrology robustness under reflectance reduction, and interleaved odd-even re-gridding mitigates residual-pattern accumulation. On single-crystal diamond, laser-microscope Sa decreased from 102 nm to 39.3 nm after 14 iterations, with a limited net removal depth. A removed-volume selectivity analysis indicates that roughness reduction saturates when protrusion removal becomes balanced by depression generation.
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Water-jet guided laser drilling of crack-free SiC through-holes
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|
Shuzo Masui, Shoichi Ui, Satoru Takahashi (1)
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STC E, 75/1/2026, P.
|
|
Keywords: Laser micro machining, Silicon carbide, laser drilling |
Abstract : Micro-scale through-holes in SiC play a crucial role in electronics and MEMS. However, drilling of crack-free and densely integrated through-holes in brittle SiC remains a major challenge. Therefore, this study demonstrated the fabrication of crack-free and chipping-less SiC through-holes by water-jet guided laser drilling. The influence of processing parameters on the cracking, chipping, processing speed, and hole dimensions was systematically investigated. Furthermore, dense arrays of crack-free through-holes, which are difficult to fabricate by conventional laser drilling, were successfully fabricated, demonstrating both the miniaturization capability and scalability of the WJGL drilling.
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|
A Print-Form-Sinter process for manufacturing 3D electronics on complex surfaces
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|
Rajiv Malhotra, Md Naim Jahangir, Hongyi Xu / B. Mullany (1)
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STC E, 75/1/2026, P.
|
|
Keywords: Sintering, Nano structure, Deformation |
Abstract : Circuits that conform to 3D surfaces enable advanced multifunctionality, miniaturization, and lightweighting. But existing manufacturing methods suffer from a tradeoff between geometric complexity, electrical performance, and throughput. This work addresses this gap by integrating printing, forming, and sintering of nanowire-based metal circuits. Experiments show the ability to go beyond the above tradeoff by achieving 30-100% greater geometric complexity and 10 times greater throughput than the state-of-the-art without significant loss in electrical performance. A multiscale multiphysical model is created to link nanowire behaviour to spatial resistivity evolution, thus revealing key process physics and creating the basis for rational process control.
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Making 3D copper shapes by spark plasma sintering with masked stereolithography salt moulds
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Markus Bambach (2), Konrad Papis, Manon Prairie
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STC E, 75/1/2026, P.
|
|
Keywords: Sintering, Powder, Additive manufacturing |
Abstract : This work demonstrates the fabrication of dense, geometrically complex 3D copper components using masked stereolithography-printed NaCl moulds as sacrificial tooling for spark plasma sintering (SPS). By tailoring the mould design and co-sintering parameters, dense copper parts with uniform equiaxed grains <25 µm diameter and dimensional deviations below 5% were achieved. An optimized sintering cycle ensured mould stability, homogeneous densification, and faithful replication of the mould geometry with a surface roughness Sa of 2.47–24 µm. Mechanical properties outperformed reported values for pure copper specimens from LPBF. The approach offers rapid processing of pure copper at low energy consumption.
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Powder stream characteristics in laser directed energy deposition of PEEK and PA12
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Daniel Nettelbeck, Sebastian-Paul Kopp, Michael Schmidt (1)
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STC E, 75/1/2026, P.
|
|
Keywords: Directed energy deposition (DED), Polymer, Powder |
Abstract : This study investigates powder stream characteristics, including powder focus and particle velocity, in laser-directed energy deposition of polymers (DED-LB/P) using high-speed imaging. PEEK and PA12, two commonly used thermoplastic powders, differ in particle morphology, flowability and thermal properties. Systematic analysis reveals strong material dependent behaviour, with PEEK exhibiting a narrower focus and higher velocities than PA12 under identical conditions. Carrier gas flow significantly affects particle velocity, while shielding gas has negligible impact. Powder flowability, particle size distribution, and the loading ratio are identified as key factors influencing powder stream characteristics, providing essential insights for optimizing polymer DED processes.
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A pressure assisted curing process for carbon fiber reinforced composites via double-sided plasma induced Joule heating
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Shuting Liu, Hongrui Yan, James Gao, Yingguang Li (2)
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STC E, 75/1/2026, P.
|
|
Keywords: Composite, Plasma, Double-sided discharge |
Abstract : A pressure assisted curing process for carbon fiber–reinforced polymers (CFRP) via double-sided dielectric barrier discharge (D-DBD) Joule heating is presented. By adopting a symmetric discharge configuration with vacuum-bag pressure, plasma-induced current was driven through the laminate, enabling internal heating while applying consolidation pressure. Compared with conventional curing, thermal uniformity was significantly improved. Through-thickness temperature difference was reduced by 92%. The cured laminated exhibited a 1.34-fold increase in interlaminar shear strength with porosity below 1.5%. Using helium gas can increase charged filaments and further improve thermal uniformity. These results proved the effectiveness of the proposed method for CFRP curing.
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Additively manufactured multi-material piezopolymer structures for actuation and sensing
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Vasileios Stratiotou-Efstratiadis, Apostolos Argyros, Giorgos Sarmas, Giannis Oikonomou, Dimitris K. Dimitriou, Ioannis Schoinas, Nikolaos A. Chrysochoidis, Dimitris A. Saravanos, Georgios Maliaris, Nikolaos Michailidis (1)
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STC E, 75/1/2026, P.
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Keywords: Piezoelectric, Material extrusion, Actuator-sensor |
Abstract : Additive manufacturing of piezoelectric devices is typically multi-step, limiting scalability and design freedom. This paper introduces a one-step multi-material-extrusion (MMEX) route that co-prints PVDF, a structural substrate, and silver-nanoparticle electrodes, followed by contact poling. Process–structure links are established by correlating MMEX parameters with electroactive (β+γ) phase fractions measured by FT-IR. Dynamic cantilever tests demonstrate bidirectional functionality: the same printed configuration acts as both actuator and sensor. A coupled electromechanical Finite Element model, calibrated against experiments, yields transferable effective d31 values and design rules for 4D-printed architected metamaterials and devices enabling rapid customization of geometry and performance tailored for applications.
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Measuring natural frequencies via vibroacoustic monitoring in laser powder bed fusion
|
|
Shivam Shukla, Rik Vaerenberg, Konstantinos Rousou, Gitte Lathouders, Elke Deckers, Konstantinos Gryllias, Bey Vrancken / J.P. Kruth (1)
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STC E, 75/1/2026, P.
|
|
Keywords: Powder bed fusion, Acoustic monitoring, Natural frequency |
Abstract : A structure-borne acoustic emission sensor attached below the base plate measured acoustic emissions during metal laser powder bed fusion additive manufacturing, after which a power spectral density analysis across the layers revealed a shift in major frequency peaks towards lower frequencies with increasing build height. The trend was analytically linked to a change in the natural frequency of the evolving printed structure and was further validated by numerical simulations. This discovery presents a potential new opportunity to use in-situ measurement of natural frequency as a part quality indicator where deviation from the theoretical natural frequency curve can indicate geometrical inconsistency or delamination.
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In-situ temperature and emissivity monitoring of blue laser powder-blown directed energy deposition of copper
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|
Jihoon Jeong, Dong Hee Kang / D.Y. Yang (1)
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STC E, 75/1/2026, P.
|
|
Keywords: Additive manufacturing (AM), Temperature, Monitoring |
Abstract : Additive manufacturing (AM) of copper is challenging due to its high thermal conductivity, low absorptivity under infrared lasers, and oxidation sensitivity. This study presents a newly integrated in-situ melt pool monitoring framework for blue laser powder-blown directed energy deposition (LP-DED) using multispectral imaging and photodiode sensing. Multispectral thermometry (MST) provides spatially resolved temperature and emissivity maps, while photodiode-based Planck thermometry (PDPT) enables high-speed radiance tracking. The measured thermal responses show strong sensitivity to laser power and shielding conditions. The combined MST-PDPT analysis reveals how variations in emissivity affect temperature interpretation. The proposed multi-sensor approach establishes a foundation for reliable real-time thermal assessment and future closed-loop process control of blue laser copper deposition.
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|
High-speed schlieren imaging of non-gaussian beam shapes in laser directed energy deposition
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Samantha Webster / F.E. Pfefferkorn (1)
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STC E, 75/1/2026, P.
|
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Keywords: Additive manufacturing (AM), Directed energy deposition (DED), Laser beam shapin |
Abstract : The objective of this work is to provide new insights into laser powder-blown directed energy deposition (DED-LB) when using non-Gaussian beam shapes by in situ gas flow visualization. This is motivated by the incomplete understanding of interaction between the laser and powder flow on melt pool formation. High-speed Schlieren imaging was implemented to visualize the effect of plume velocity on particle flow for seven beam distributions and demonstrates that 450 µm feature sizes can be achieved. The plume velocity ranged from 0.5 m/s to 16 m/s, and three regimes of behavior were identified as beams transitioned between Gaussian and annular distributions.
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Identification of coexisting dynamic coupling regimes in high-speed directed energy deposition
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Patrick Gajek, Helena Wexel, Frederik Zanger (2)
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STC E, 75/1/2026, P.
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Keywords: Additive manufacturing (AM), Monitoring, Photometric emission |
Abstract : High-speed directed energy deposition (HS-DED) fundamentally alters laser–material interaction dynamics due to coexisting fast plasma-related and delayed thermal responses, complicating process stability in transition regimes. This work investigates the dynamic behaviour of AISI 316L processed on a commercial HS-DED system. It is shown that conventional grey-box models based on spatially integrated photometric signals fail to describe the process response at critical operating points. Using multispectral photometric measurements, the emission signal is temporally separated into plasma-related and thermal components. Based on this, a time-domain metric termed spectral lag is introduced, providing an emissivity-independent indicator that reliably captures regime transitions.
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Solid-state transformations during laser directed energy deposition of Ti-6Al-4V powder hydride-dehydrided from scrap metals
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Sarah J. Wolff, Marwan Haddad, Rama Diop, Andrew C. Chuang / L. Fratini (1)
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STC E, 75/1/2026, P.
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Keywords: Additive manufacturing (AM), Titanium, In-situ phase transformation |
Abstract : During laser directed energy deposition (DED-LB), thermal cycling and powder chemical composition produce distinct thermal histories, which vary mechanical properties. Using real-time X-ray diffraction, this study investigates solid-state transformations during DED-LB to understand process-structure-property relationships for angular Ti-6Al-4V powder hydride–dehydrided from scrap metals. Results showed that regions near the molten pool experienced high cooling rates, leading to martensitic transformation from the β phase and increased hardness. Regions farther from the molten pool underwent tempering without solid-state transformation and decreased hardness. These findings support alternative feedstocks for metal additive manufacturing for a circular economy and resilient supply chains.
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Multi-material laser powder bed fusion of high-strength, high-ductility SiC-reinforced 316L stainless steel metal matrix composites
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|
Yuan-Hui Chueh, Yi-Cheng Lee, Guo-Chi Li, Chao-Chieh Hsu, Albert J. Shih (1)
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STC E, 75/1/2026, P.
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|
Keywords: Additive manufacturing, Selective laser melting (SLM), Multi-material laser powder bed fusion |
Abstract : Laser powder bed fusion (LPBF) fabricated ceramic particle–reinforced metal matrix composites (MMCs) offer high strength but suffer from low ductility. This study explores a nacre-like brick-and-mortar architecture enabled by multi-material LPBF to mitigate this limitation by integrating SiC-reinforced 316L stainless steel (SS) MMC as bricks with the ductile 316L SS as mortar. Interfacial microstructural analysis revealed cellular-to-dendritic transitions and stable bonding in MMC at 6 vol% SiC. Compared with the 1201 MPa strength and 7.3% elongation of 6 vol% SiC MMC, the interlocking brick-mortar architecture maintained strength at 1150 MPa while increasing ductility by 157% to 18.0%.
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Using single pulses in powder-blown directed energy deposition to fabricate high-aspect-ratio metal pins
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Wessel W. Wits (2), Shenliang Yang, Jos Vroon, Scholte J.L. Bremer
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STC E, 75/1/2026, P.
|
|
Keywords: Additive manufacturing (AM), Directed energy deposition (DED), High-aspect-ratio metal pins |
Abstract : This study investigates the fabrication of high-aspect-ratio metal pins using powder-blown directed energy deposition. Pins are deposited by consecutive laser pulses using titanium alloy Ti6Al4V as feedstock material. A physics-integrated experimental-analytical-numerical framework is developed to predict pin geometry, pin growth and thermal history during fabrication. The framework combines experimental in-situ temperature measurements, an analytical geometry model, and a finite element thermal model for melt pool lifetime predictions. Results show good agreement between model predictions and experimental observations, enabling controlled constant-diameter vertical pin growth with optimised process parameters, which is crucial for applications such as hybrid metal-composite joining and structural repair.
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Methodology for in-track grading in DED-LB by time-dependent powder feeder control
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Lars Bachert, Jacques Platz, Jan C. Aurich (1)
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STC E, 75/1/2026, P.
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Keywords: Additive manufacturing (AM), Directed energy deposition (DED), In-track grading |
Abstract : This study demonstrates continuous chemical grading of 316L and 17-4PH stainless steels within a single welding track in laser-based Directed Energy Deposition (DED-LB) by exploiting the transition between two powders. Transition- and response times of the powder flows were experimentally determined and incorporated into path planning to achieve grading within a single welding track. In-track gradients were confirmed by energy-dispersive spectroscopy (EDS) and hardness profiles. Relative densities above 99% were achieved. The results demonstrate that in-track grading is reproducible without hardware modification and transition times scale proportionally with feeder rotation speed while response time remains nearly equal.
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STC F |
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Towards constant wall thickness in hybrid single point incremental forming
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Carlos M.A. Silva, Rui F.V. Sampaio, João M.A. Viegas, João P.M. Pragana, Ivo M.F. Bragança, Paulo A.F. Martins (1)
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STC F, 75/1/2026, P.
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Keywords: Incremental sheet forming, Hybrid manufacturing, Backward point projection method |
Abstract : This paper explores the hybridization of single-point incremental forming (SPIF) with metal cutting to produce parts with uniform wall thickness profiles. The proposed manufacturing approach involves machining tailored blanks from thicker sheets or plates, with the initial thickness profile determined through analytical modelling using a software developed by the authors, which utilizes a backward implementation of the point projection method, previously used to predict the final wall thickness of conventional SPIF parts. The new hybrid SPIF approach is validated through experimental test cases, and a proof-of-concept aeronautic component with uniform wall thickness is fabricated to demonstrate its effectiveness.
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Improving geometric accuracy of double-sided incremental forming using machine learning
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Shayan Darzi, Abrar S. Ebrahim, Brad L. Kinsey (1), Jinjin Ha
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STC F, 75/1/2026, P.
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Keywords: Tool path, Incremental sheet forming, Machine learning |
Abstract : Double-sided incremental forming (DSIF) is a dieless sheet-forming process, which like all metal forming processes is limited by springback-induced geometric deviation. In this work, an artificial neural network (ANN) framework is developed to predict geometric deviation across varying geometries, materials, and thicknesses using geometry descriptors and material properties. The ANN model is trained on 25 parts spanning five geometries and five materials and is evaluated on a part with unseen geometry, material, and thickness, achieving a mean absolute prediction error of 0.57 mm. A compensated toolpath is created according to the predicted deviation, reducing the mean absolute deviation by 54%.
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Incremental profile forming with axial stress superposition
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Yannis P. Korkolis, Markus Stennei, A. Erman Tekkaya (1)
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STC F, 75/1/2026, P.
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Keywords: Profile forming, Accuracy, Stress superposition |
Abstract : The incremental profile forming process enables the flexible forming of profiles with axially varying cross-sections. The localized complex deformation field induces large shape deviations. It is hypothesized that the shape accuracy can be improved by stress superposition. For the fundamental case of axial groove forming, several stress superposition modes are examined. Axial stress superposition is shown to be the most effective one: an axial tensile stress of the order of the initial flow stress improves the shape accuracy by a factor of 20, while the steady-state indentation and axial forces are reduced by approx. 30-55%.
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Modelling of instability defects in thermo-bending of polymer-based tubes
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Enrico Simonetto, Stefania Bruschi (1), Takashi Kuboki (1), Andrea Ghiotti (1)
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STC F, 75/1/2026, P.
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|
Keywords: Tube, Bending, Thermal control |
Abstract : This study presents an integrated experimental–numerical framework to predict and mitigate instability defects in thermo-bending of polymer-based tubes. A differential local thermal control system was developed to regulate thermo-mechanical behaviour across the glass transition temperature. A modified constitutive model was calibrated for polyamide 12 (PA12) and polyvinyl chloride (PVC), capturing strain softening and hardening regimes. Results show that PA12 provides a wide processing window, while PVC requires asymmetric heating to shift the neutral axis and suppress wrinkling, necking, and ovalization. The framework enables reliable prediction and improved control of thermo-bending processes.
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Increasing material utilization in cup forming by folding-shearing
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Rishabh Arora, Omer Music, Julian M. Allwood (1)
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STC F, 75/1/2026, P.
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|
Keywords: Sheet metal, Deep drawing, Folding-shearing |
Abstract : The global beverage-can industry scraps up to 15% of purchased material creating both financial and environmental costs. This scrap arises primarily when cutting circular blanks from rectangular sheets. This study explores can-making from tessellating hexagonal blanks using the folding-shearing process with a new trapezoidal beak geometry. A systematic investigation across a range of geometric variables leads to definition of an operating window connecting beak design to the onset of fracture via material locking in the tools. Cylindrical cups up to 35 mm in height are produced in nearly pure-shear deformation with minimal thinning and wrinkling, reducing material waste by ~30%.
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|
Adaptive tooling system for enhanced process stability and punch longevity in ironing
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|
Kaarel Siimut, Kasper M. Madsen, Ermanno Ceron (3), Chris V. Nielsen (2)
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STC F, 75/1/2026, P.
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|
Keywords: Metal forming, Process control, Adaptive tooling |
Abstract : Industrial-scale tests on a progressive forming tool with an adjustable-diameter ironing punch are presented. The punch diameter was controlled stroke-to-stroke by a PID loop using on-line cup height feedback. The system maintained constant cup height despite changing tool temperature and strip thickness that cause >6% cup height change with a conventional punch. Using an environmentally benign lubricant at an elevated production rate, the conventional punch produced defective parts after 1200 strokes and failed after 2860, while the adjustable punch completed 6000 strokes without breakdown. The adaptive tool simultaneously improved process stability, part quality, productivity, and environmental footprint in high-volume ironing.
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Influence of distortion on the formability of tailored blanks produced by directed energy deposition
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Raphaela März, Marion Merklein (1)
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STC F, 75/1/2026, P.
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Keywords: Deep drawing, Directed energy deposition (DED), Tailored additive blanks |
Abstract : Additive manufacturing allows for local reinforcement of sheet metal. One process limitation when using directed energy deposition (DED) is the distortion caused by thermal effects. In order to better understand the distortion of sheet metal components, the influences of process and workpiece on the distortion are analyzed. Tailored additive blanks with different degree of distortion are deep drawn in order to investigate the influence of distortion on the formability. The experimental results show that although the DED induces significant distortion which can compromise blank positioning, the subsequent deep drawing can compensate this distortion, enabling robust utilization of tailored additive blanks.
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Design of spatially and temporally variable blank holding forces based on Bayesian optimization for aluminum pouch forming
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|
Taegyun Ahn, Taek Jin Jang, Cheol Sagong, Jeong Whan Yoon (2)
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STC F, 75/1/2026, P.
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|
Keywords: Forming, Process control, Bayesian optimization |
Abstract : In pouch forming for lithium-ion battery cell, deep forming without fracture is challenging due to severe strain localization under uniform and constant blank holding force (BHF). To address this, variable BHF is introduced. This study proposes a simulation-efficient framework for designing spatially and temporally variable BHF using Bayesian optimization. A slit-structured blank holder enabling local force modulation was employed, and formability was evaluated without relying on a conventional forming limit curve by defining a practical target region on the thinning limit diagram. Cross-sectional measurements at the critical region showed good agreement between simulated and experimentally measured residual aluminum thickness.
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Local formability of advanced high-strength steels: Role of damage tolerance and microstructural heterogeneity
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|
Yuling Chang, Rongfei Juan, Zinan Li, Wolfgang Bleck, Junhe Lian / G. Hirt (1)
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STC F, 75/1/2026, P.
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|
Keywords: Forming, Blanking, Edge fracture |
Abstract : Advanced high-strength steels (AHSS) often exhibit a trade-off between global and local formability. This study investigates five AHSS grades to elucidate microstructural factors governing local formability and propose a quantitative metric for damage tolerance. Shear-induced edge damage is correlated with the hole-expansion ratio (HER). An integrated approach combining high-throughput nanoindentation mapping with the effective heterogeneity index (EHI) captures hardness distribution disorder and mechanical contrast. EHI correlates strongly with the HER, effectively predicting local formability and damage tolerance of multiphase steels. This proposed approach offers a new tool for designing AHSS with an optimal balance between strength, ductility, and damage tolerance.
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JAX-FORGE: GPU-accelerated high-fidelity simulation for incremental open-die forging
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Colton Wright, Fanglei Hu, Joshua Groves, Deepak Sharma, Brian Thurston, Glenn Daehn, Michael Groeber, Jian Cao (1)
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STC F, 75/1/2026, P.
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Keywords: Metal forming, Hot deformation, Rapid GPU-accelerated simulation |
Abstract : This work presents an incremental open-die forging platform, Agility Forge, to enable flexible high-mix manufacturing. Additionally, the platform can be utilized to characterize material property at high temperature through the differentiability of a GPU-accelerated finite element platform JAX-FEM, which incorporates fully coupled thermomechanical behaviour at finite strain and temperature-dependent material parameters. JAX-Forge, built on JAX-FEM, develops a seamless interface for multi-hit forging operation. The framework is validated by reproducing the Agility Forge robotic forging process and compared with experimental measurements via laser profilometer. JAX-Forge constitutes a core component of a broader simulation ecosystem for process planning.
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In-process micro-forging enhanced additive manufacturing of Inconel 718 with significant grain refinement
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Sulin Chen, Zekai Liu, Zeshen Zhuang, Bin Shen, Wansheng Zhao (2), Lin Li (1)
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STC F, 75/1/2026, P.
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Keywords: Additive manufacturing (AM), Processing, Surface integrity |
Abstract : Inconel 718 components fabricated via directed energy deposition (DED) are often constrained by inherent technological defects, limiting their strength-toughness performance compared to conventionally forged materials. This study presents a novel high-frequency micro-forging technique integrated with DED, enabling IN718 to achieve an ultimate tensile strength of 1421 MPa. Comprehensive microstructural analysis reveals that the substantial strength improvement is primarily attributed to the synergistic effects of grain refinement (approximately 3.3 µm), uniformly distributed γ'' precipitates along grain boundaries, and a high density of twin boundaries.
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STC G |
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A novel bonnet polishing approach with a vision-based sensor for in-situ characterization of contact force distribution and pose misalignment
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Feiyu Zhang, Jieji Ren, Langlang Yuan, Mengqi Rao, Yuehong Yin (1)
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STC G, 75/1/2026, P.
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Keywords: Polishing, In-process measurement, Vision |
Abstract : Pose misalignment in bonnet polishing induces contact pressure distortion, impairing process determinism. However, conventional force sensing techniques lack the capability for in-situ spatial contact characterization. This paper proposes a novel vision-based sensor utilizing inner-surface embedded markers. By capturing the markers' 3D displacement field via a vision module, the system achieves precise quantification of contact force distribution and robust identification of pose deviation. Case studies demonstrate the sensor's high sensitivity within the micro-angle range. With visual feedback correction, the polished surface RMS improved significantly from 57.7 nm to 11.1 nm, validating the method's efficacy in enhancing process determinism.
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Morphologies, formation mechanisms, and mitigation strategies of groove-type scratches and ridge-type traces in slurry-less ECMP of 4H-SiC
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Rongyan Sun, Aoi Kaneko, Yuji Ohkubo, Kazuya Yamamura (2)
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STC G, 75/1/2026, P.
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Keywords: 4H-SiC, Slurry-less ECMP, Ridge-type traces, Oxidation mechanism |
Abstract : 4H-SiC wafers require damage-free, ultra-smooth surfaces for power devices manufacturing, whereas conventional chemical mechanical polishing (CMP) often suffers from limited throughput and high cost. Slurry-less electrochemical mechanical polishing (ECMP) enables efficient smoothing with low cost, but surface scratches still limit surface integrity and yield. This study systematically observed and classified surface morphologies formed on 4H-SiC under different ECMP conditions, including conventional groove-type scratches and ECMP-specific ridge-type traces, and elucidated the mechanisms underlying each type. Based on these insights, practical process-optimization strategies were proposed to suppress trace formation and improve slurry-less ECMP stability and applicability.
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One-step hybrid adaptive polishing using shear-thickening fluid for nanometric surface finish on additively manufactured metallic surfaces
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Chunjin Wang (3), Zhen Ma, Chi Fai Cheung (1), Alborz Shokrani (2), Song Yuan
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STC G, 75/1/2026, P.
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Keywords: Polishing, Additive manufacturing, Hyrid Adaptive |
Abstract : Achieving nanometric surface finish on additively manufactured parts with high roughness and complex geometries typically requires multiple polishing steps with low efficiency. This paper presents a one-step hybrid adaptive polishing method that integrates a flexible polishing tool with a bonded diamond abrasive cloth and a shear-thickening Al₂O₃ slurry fluid, enabling both shape adaptive and a seamless transition from two-body to three-body material removal. Experiments on stainless steel and titanium alloy demonstrate one-step polishing with arithmetical mean height below 50 nm. Mechanism analysis reveals that the dynamic balance between contact and fluid pressures drives wear- state evolution, achieving nanometric surface finish.
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New graphene-enhanced shear-thickening polishing slurry
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Min Li, Bernhard Karpuschewski (1), Oltmann Riemer, Yunlong Li, Ting Dong
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STC G, 75/1/2026, P.
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Keywords: Polishing, Material removal, Shear thickening |
Abstract : This work develops a new graphene-enhanced shear-thickening polishing slurry (GE-STPS) for ultraprecision finishing of sapphire. The incorporation of graphene nanosheets strengthens hydrodynamic lubrication and enhances viscosity, modulus, and strain-rate sensitivity while preserving the reversible thickening behaviour. Polishing experiments show that adding 10 wt.% graphene reduces the surface roughness from Ra 150 nm to 29 nm, confirming its superior polishing capability. Molecular dynamics simulations further demonstrate that graphene helps suppress debris formation and subsurface dislocation generation. Consequently, GE-STPS enables efficient, stable, and damage-controlled polishing of hard and brittle crystalline materials.
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Effect of dressing on the process mechanics and material separation mechanisms in finishing of cemented carbides with fine diamond grinding wheels
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Monika Kipp, Philipp Hoier, Peter Krajnik (1), Dirk Biermann (1)
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STC G, 75/1/2026, P.
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Keywords: Grinding, Dressing, Finishing |
Abstract : Finishing of WC–Co cemented carbides with resin bonded fine diamond grinding wheels was studied with emphasis on dressing. The variation of dressing conditions generated grinding wheel topographies from smooth, plateau-like to rough, quantified by areal surface texture parameters. Analysis of forces, specific grinding energy and surface roughness establishes how dressing-defined grinding wheel topography governs finishing behaviour. Smooth grinding wheel conditions yielded the lowest workpiece roughness but higher forces and specific grinding energy, whereas rough grinding wheel conditions reduced mechanical load and energy at the expense of surface finish. SEM revealed Co-binder smearing and WC-grain flattening on the finished surfaces.
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Continuous variable-speed grinding for no-lead surface generation
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Maria Garcia-Moreno (3), Jorge Alvarez, David Barrenetxea (1), Monica Gil-Inchaurza, Iñigo Pombo
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STC G, 75/1/2026, P.
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Keywords: Grinding, Dressing, Lead, Variable-speed |
Abstract : This study investigates continuous variable-speed grinding as a method for achieving no-lead surfaces on cylindrical workpieces. Experimental tests compare conventional and continuous variable infeed and workpiece speed cycles across diverse dressing-grinding conditions, demonstrating that continuous speed variation reduces lead depth and often produces zero-angle lead when non-integer speed ratios or higher dressing overlaps are used. A 3D kinematic model is developed to simulate continuous variable-speed operation, accurately predicting thread number, angle, and lead pattern depth trends. The study shows that wheel-imbalance harmonics significantly influence zero-angle lead patterns. Results confirm continuous variable-speed strategies as an effective approach to achieve no-lead surfaces.
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Analytical and experimental investigation of subsurface characteristics and their depth-dependent modifications in grinding of case-hardened steel
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Gerrit Kuhlmann, Lars Langenhorst, Martin Hunkel, Tobias Hüsemann, Carsten Heinzel (2)
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STC G, 75/1/2026, P.
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Keywords: Grinding, Simulation, Case Hardening |
Abstract : This study investigates the influence of depth-dependent microstructural differences in case-hardened workpieces on process loads and subsurface characteristics. Specimen preparation using EDM and polishing enables analysis of hardness depth profiles and microstructural modifications after single-stage grinding for different depths within the case-hardened layer. Results show reduced modification depths for deeper levels. To understand underlying mechanisms, phase fractions (martensite, retained austenite, cementite) and hardness depth profiles were calculated analytically. Carbon-dependent softening of martensite is the main factor influencing hardness modification depths. In two-stage grinding, measurements and simulations reveal depth-dependent increased modification depths due to roughing and reduced loads in finishing.
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Smoothed particle Galerkin (SPG) modeling of microcrack formation in diamond grinding silicon carbide fiber-reinforced silicon carbide (SiCf/SiC)
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Chunlei K. Song, Sebastian Prinz, Raj Kachhadiya, Thomas Bergs (2), Albert J. Shih (1)
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STC G, 75/1/2026, P.
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Keywords: Silicon carbide, Grinding, Microcrack modeling |
Abstract : This study investigates the smoothed particle Galerkin (SPG) method for modeling microcrack formation in diamond grinding of silicon carbide fiber-reinforced silicon carbide (SiCf/SiC) composites. The SPG method defines material separation by deleting inter-particle bonds rather than using element deletion or particle erosion as in finite element method or smooth particle hydrodynamics modeling. This bond-based failure model preserves the workpiece mass, enabling accurate and stable simulation of microcrack formation. Parallel computing, combined with an optimal domain decomposition strategy, is used to mitigate the extensive computational cost. SPG predicted microcracks align well with observations from scanning electron microscopy and transmission electron microscopy.
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Mechanistic linkage between media–workpiece interaction and surface topography in gyro finishing with spherical alumina media
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Yohei Hashimoto, Kenta Miyake, Tetsuya Yamada, Minoru Ito / Y. Takeuchi (1)
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STC G, 75/1/2026, P.
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Keywords: Finishing, Mechanism, Mass finishing |
Abstract : Gyro finishing uses an abrasive-media flow in a rotating vertical barrel to finish complex parts held in the media flow. This study established a mechanistic link between media–workpiece interaction and surface topography for spherical alumina media. Time-resolved mark observations and high-rate single-medium force measurements validated that intermittent impulsive loading dominates dent-type surface generation under the present conditions, whereas short-time media-motion observations suggested rapid force transmission from rear-side media as the origin of the loading. Furthermore, the surface evolution was predicted based on the measured dent-type mark statistics, linking the interaction to the macroscopic finishing performance.
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STC M |
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A physics-guided data driven method for sensorless measurement of cutting forces using CNC servo drive signals
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Chung-Yu Tai, Yusuf Altintas (1)
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STC M, 75/1/2026, P.
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Keywords: Force, Feed drive, CNC |
Abstract : Cutting forces are essential for monitoring tool condition, process loads, and machining abnormalities. This paper presents a physics-guided deep learning approach for sensorless estimation of cutting forces using motor current commands. The method accounts for inertia, gravity, speed- and load-dependent friction, and drive cross-talk effects. A neural network is trained using CNC-collected velocity, acceleration, and motor current signals, together with dynamometer-measured cutting forces. Once trained, the network predicts cutting forces directly and in real time from CNC data. The approach is validated through machining experiments on an industrial part.
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Precision force control with observer-based vibration compensation for conformal vibration polishing
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Jixiang Yang, Xu Tang, Wenhao Li, Han Ding, Zhigang Wang (2), Yuehong Yin (1)
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STC M, 75/1/2026, P.
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Keywords: Vibration polishing, Force control, Vibration compensation, Spatial-frequency suppression |
Abstract : This paper presents an observer-based vibration-compensated precision force control method for force-controlled conformal vibration polishing (FCVP) in optical surface fabrication. A material removal model is established to reveal the spatial-frequency error suppression mechanisms of FCVP. A force-vibration generation unit enabling stable normal force regulation and controllable tangential vibration is developed. An observer-based vibration-compensated force control method is integrated to suppress vibration-induced disturbances and enhance force regulation accuracy under vibratory conditions. Polishing experiments demonstrate that the improved force control significantly enhances surface figure accuracy and suppresses spatial-frequency errors, thereby verifying the effectiveness of FCVP for ultra-precision optical finishing.
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Surrogate modelling in axles rolling processes
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Zoltan Dombovari, Attila Szlancsik, Kristof Bobor, Gabor Henap, Lander Galdos, Ruben Merino, Gabor Stepan (1)
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STC M, 75/1/2026, P.
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Keywords: Cold forming, Rolling, Finite element method (FEM) |
Abstract : A surrogate analytical model was constructed and validated for deep rolling in train axle production. Two independent, distinct finite element models were developed to simulate both the time evolution and the stationary solution of this cold forming process. To reduce computational time, an efficient surrogate model was fitted that captures key features observed in the finite element modelling, such as the hardening relay and a maximum in the forming force characteristics as a function of feed rate. A measurement setup was developed for validation with pull-off roller ditch depth measurement.
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On-machine tool wear monitoring system using strain-gauge signals and edge force coefficients with physics-informed machine learning
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Mahdi Mohamadyari Heydarlou, Arash Ebrahimi Araghizad, Yuki Yamada, Haythem Boujnah, Naruhiro Irino (2), Erhan Budak (1)
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STC M, 75/1/2026, P.
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Keywords: Wear, Machine learning, Edge force coefficient |
Abstract : This paper presents a hybrid framework for tool wear monitoring in milling integrating strain sensor-based force measurement signals (SSFM), mechanistic force-coefficient identification, and machine learning (ML). Strain sensors and dynamometer signals train ML models that estimate cutting forces across various cutting conditions. Reconstructed forces feed an inverse mechanistic model to estimate cutting and edge coefficients over tool life. These coefficients are then used by an XGBoost model to predict in-process flank wear. Experiments across multiple cutting conditions demonstrate real-time estimation, accurate force prediction, and reliable wear estimation, showing that physics-informed features improve robustness and production compatibility.
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Simultaneous identification of milling and structural dynamics parameters under stable cutting using table-side disturbance forces
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Koki Matsubara, Hideyuki Fujii, Yasuhiro Imabeppu, Naruhiro Irino (2), Norikazu Suzuki (2)
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STC M, 75/1/2026, P.
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Keywords: Machining, Milling, Dynamics |
Abstract : This study proposes a novel identification method that excites asynchronous uncut chip thickness variations under stable conditions, without inducing chatter vibrations. The accuracy of milling simulation depends on accurate identification of model parameters. Existing in-process identification methods require weak chatter vibrations to generate asynchronous variations, which limits their applicability in practical machining. Using only disturbance forces measurable at the table side, the proposed method simultaneously identifies cutting parameters and structural dynamic parameters. Numerical simulations and cutting experiments demonstrate that the identified parameters agree with those obtained by conventional offline methods, confirming the validity and practical applicability of the proposed approach.
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On the effect of process stiffening and process damping on milling dynamics
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Florian Wöste, Jonas Baumann, Timo Platt, Felix Niggemeyer, Petra Wiederkehr (2)
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STC M, 75/1/2026, P.
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Keywords: Milling, Damping, Process stiffening |
Abstract : The dynamic contact between the flank face of the tool and the workpiece surface can affect process stability and prevent chatter. Such an interaction is typically interpreted as process damping and, thus, as dissipative, but can also have a distinct stiffening effect. In this work, the impact of both process stiffening and process damping on the dynamics and stability of milling processes is investigated, considering different spindle speeds and engagement conditions. Specifically modified tools were used for this purpose, including those with conventional and structured flank face chamfers, which led to significantly different characteristics of the flank face interactions.
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Stability prediction of 5-axis milling of thin walls by means of semidiscretization
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Markel Sanz-Calle, Leire Arrieta-Lizarazu, Alexander Iglesias, Mikel Zatarain (1)
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STC M, 75/1/2026, P.
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Keywords: Milling, Modelling, Chatter |
Abstract : Semidiscretisation is a well-known method for stability prediction in milling which provides a quantitative measure of stability very convenient for optimization purposes. Existing approaches have extended it to 5-axis cases or varying thin wall dynamics, but none of them have provided a robust workflow to simulate and optimize real industrial scenarios. This work presents a 5-axis milling stability framework combining a tri-dexel engagement model, an automatic finite element model of the workpiece, and semidiscretization, enabling process optimization. The approach is applied to an industrial case, where a mark caused by surface location error is mitigated while keeping the process stable.
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Physics-driven real-time, intelligent digital twin for adaptive milling chatter control
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Yi Huang, Jingang Yi, Yuebin Guo (1)
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STC M, 75/1/2026, P.
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Keywords: Digital twin, Chatter, Physics-informed machine learning |
Abstract : Milling chatter is a lasting issue that significantly affects surface quality and tool life. Although conventional chatter prediction models are well established, real-time adaptation remains challenging when the in-process dynamics vary. This work presents a real-time digital twin, driven by physics-informed machine learning models, to predict and adaptively suppress milling chatter. A stability lobe diagram (SLD)-based digital twin is updated with online force data and adaptively tunes the spindle speed and the feed rate. Compared to the offline, static SLD baseline, the online, dynamic digital twin synchronizes with time-varying process conditions in real time and adaptively adjusts process parameters to maintain stability while regulating milling forces.
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Influence of bearing and coupling characteristics on stability of a feed drive system
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Ryuta Sato / T. Moriwaki (1)
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STC M, 75/1/2026, P.
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Keywords: Feed drive, Stability, Bearing |
Abstract : In machine tools, feed drives are typically driven by ball screws. Higher controller feedback gains are always required; however, they destabilize the system related to the characteristics of the mechanism. In this study, the influence of stiffness and damping of the support bearing and coupling on the stability of a feed drive system is investigated via experiments and simulations. It is clarified that the oscillatory vibration mode is changed by balancing these parameters when the higher gains are applied. Additionally, a novel “stability map” is proposed based on the pole placement analysis to show suitable ranges of the parameters.
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Model-based laser preheating control for high-speed Directed Energy Deposition (DED) pipe coating
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Kezi Li, Shiho Takemura, Burak Sencer (2), Ryozo Nagamune, Yasuhiro Kakinuma (1)
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STC M, 75/1/2026, P.
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Keywords: Additive manufacturing (AM), Directed energy deposition (DED), Temperature, Control |
Abstract : The high-speed Directed Energy Deposition (DED)-based pipe coating process promises great productivity but suffers from steep thermal gradients that promote cracking. This paper proposes a controlled laser preheating strategy to shape the spatial thermal distribution before coating. A physics-based thermal dynamics model for control design is presented that captures conduction, heat losses, and the moving laser source, and it is calibrated through on-machine thermal response tests. The model is then used to jointly pre-schedule the laser power and traverse velocity to achieve desired temperature profiles. Experimental results verify the model accuracy and the effect of controlled preheating on crack suppression.
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On-machine measurement of thermal displacement using a robot-assisted dual-comb ranging system
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Shun Tanaka, Yuta Teshima, Naohiko Sugita (1)
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STC M, 75/1/2026, P.
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Keywords: Machine tools, Thermal error, Measurement |
Abstract : Thermal displacement in machine tools affects machining accuracy, and its compensation requires periodic measurement under operational conditions. This paper proposes a robot-assisted dual-comb ranging (DCR) system that leverages the wide ambiguity range of optical frequency combs to measure relative drift between a tool holder and a workpiece fixture without reflectors, thereby reducing setup time compared with conventional methods. Verification on a three-axis machining center demonstrated micrometer-order displacement measurement within <1 min during idle operation. Discrepancies observed after machining suggest spatially non-uniform deformation due to temperature gradients. Future work will focus on extending 3D evaluation and automatic compensation model updates.
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Pre-compensation of machining part programs for high-accuracy trajectory generation
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Shih-Hsuan Chien, Shingo Tajima, David Wilkinson, Burak Sencer (2)
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STC M, 75/1/2026, P.
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Keywords: Computer numerical control (CNC), Machine learning, Compensation |
Abstract : Modern CNC systems employ proprietary trajectory generation algorithms that smooth part programs but in turn introduce “interpolation errors” in the actual tool motion. This paper presents a pre‑compensation strategy that modifies the original part program to reduce these errors. First, a model‑based approach is introduced, and the toolpath is modified based on the known interpolation dynamics of the NC system. Next, the method is generalized using reinforcement learning (RL), which enables data‑driven compensation without requiring an analytical model. Experimental results demonstrate a two-fold improvement in interpolation accuracy while preserving the original cycle time.
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Micro-dosing system for space-resolved multi-material PBF-LB/M processes
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Hans-Christian Möhring (1), Sohan Acharya, Adrian Fried
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STC M, 75/1/2026, P.
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Keywords: Machine tool, Additive manufacturing (AM), Multi-material |
Abstract : The realization of space-resolved multi-material structures in laser powder bed fusion of metals (PBF-LB/M) is constrained by the limited capability of conventional systems to introduce secondary materials at defined locations within a build. Here, a machine integrated micro-dosing system for the deposition of secondary powders during the additive manufacturing process is introduced, that allows a controlled placement of small powder quantities providing flexibility in spatial resolution and deposited mass. Experiments show the capability of the system using Inconel 718 as base material and Maraging Steel as secondary powder. The approach enables the fabrication of functionally integrated components for various applications.
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Near-field acoustic gripping for contactless semiconductor die handling
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Yaoke Wang, Ziming Zhao, Yi Shi, Ping Guo (2)
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STC M, 75/1/2026, P.
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Keywords: Handling, Ultrasonic, Near-field acoustic |
Abstract : This study presents near-field acoustic gripping for contactless semiconductor die handling. Existing near-field acoustic attraction fails for larger objects because repulsive squeeze pressure overwhelms attractive edge effects. A mechanistic model resolving these competing forces is presented to explain the geometric size constraint. To address the size limitation, a scalable multi-island design that segments the air film is proposed to maintain the attractive regime. Experiments demonstrate stable pickup of an 8 by 8 millimeter silicon die, doubling the known size limit. The system achieves a high vertical stiffness of 522 N/m and withstands 0.7 g lateral acceleration, validating its potential for advanced packaging.
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Implementation of gear shaping on multi-tasking machine tools
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Kotaro Mori (2), Minoru Tanemoto, Hiroya Ishiyama, Woelk Eugen
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STC M, 75/1/2026, P.
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Keywords: Gear, Cutting, Shaping |
Abstract : Currently, special-purpose machines equipped with a pinion cutter (gear shaper) are mainly used for gear shaping. Process integration is highly desirable. However, integration of gear shaping process is still not common. This study presents gear shaping on multi-tasking machine tools. The motion of gear shapers is reproduced on a mill-turn machine. New cycles that utilize linear axes motion are also investigated. Although the achieved cycle time is longer than that of a gear shaper, the proposed cycle offers the shortest possible cycle time while maintaining acceptable accuracy.
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Development of a multi-phase spindle motor with active damping for chatter reduction
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Steffen Ihlenfeldt (2), Dennis Guhl, Damian Anders, Lars Penter
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STC M, 75/1/2026, P.
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Keywords: Active damping, Milling, Spindle motor |
Abstract : High chip removal rates in machining are often limited by chatter vibrations. While active damping in spindles may mitigate chatter, existing approaches reduce the drive power by occupying axial space. The ratio of damping to drive power is fixed, which limits in-process adjustability. This study proposes a novel spindle concept featuring a ‘bearingless’, multi-phase motor, enabling simultaneous high-performance drive characteristics and adaptive active damping without compromising spindle length or power capacity. Multi-phase motors are typically investigated at power levels below 10 kW, constraining their applicability to high-performance machining. In contrast, this study realized the concept by rewinding the stator of a commercially available 25 kW spindle. Experimental validation demonstrated a reduction in shaft deflection in response to frequency disturbances up to 650 Hz, with no impact on spindle speed, indicating significant potential for chatter reduction.
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STC O |
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Condition-based scheduling for EV battery remanufacturing under uncertainty
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Xingyu Li, Aydin Nassehi (1)
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STC O, 75/1/2026, P.
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Keywords: Scheduling, Optimization, Remanufacturing |
Abstract : This study formulates a Condition-Based Battery Remanufacturing Scheduling (CBRS) problem to address uncertainties inherent in electric-vehicle battery remanufacturing, where internal module conditions are unknown prior to disassembly. Such uncertainties create challenges in determining the interdependent routing, machine assignment, and operational decisions. To address these challenges, we develop risk management methods to minimize makespan and maximize recovered value while explicitly controlling the risk of route nonviability. The proposed methods improve the robustness of decision-making and consistently outperform heuristics, including Shortest Processing Time and the proposed Smallest Module Requirement, achieving up to 34.6% higher recovered value while reducing makespan by approximately 50%.
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Production quality control of mechanical recycling systems for specification-compliant circular manufacturing of fiber-reinforced polymer products
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Marcello Colledani (1), Giacomo Bonaiti, Cortinovis Fabio, Marco Diani
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STC O, 75/1/2026, P.
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Keywords: Modelling, Control, Circular Manufacturing |
Abstract : Fiber-reinforced polymer products are widely adopted in several industries, although their circularity remains a concern. Mechanical recycling is emerging as a viable solution to obtain mixed fiber-resin granules, suitable for reprocessing into new composite-made parts. However, each reprocessing application demands specific secondary material properties, calling for high adaptability of the recycling system delivering these output fractions. This paper presents a methodology to control mechanical recycling systems to meet desired throughput and particle size specifications, customized to the reprocessing application. The industrial benefits are validated in a real business case focused on circular manufacturing of composite-made electro-mechanical parts.
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Dynamic reassembly control in flexible remanufacturing systems using ant colony optimisation
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Finn Bail, Nicole Stricker, Jonas Schwenker, Marcello Urgo (2), Gisela Lanza (1)
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STC O, 75/1/2026, P.
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Keywords: Adaptive Control, Remanufacturing, Scheduling |
Abstract : Remanufacturing demands flexible operational management because fluctuations in return volumes, component conditions, and processing durations can spread through the process steps and quickly undermine fixed plans. While research has largely focused on disassembly, dynamic control of reassembly remains neglected despite its variant-dependent matching requirements. This paper proposes a new Ant Colony Optimisation (ACO) formulation that treats reassembly as a sequential decision-making process, rather than building complete schedules, employing pheromone adaptation to guide effective matching decisions under uncertainty. Embedded within a discrete-event simulation model, the proposed single-shift approach is evaluated across scenarios of increasing complexity. Results show substantially improved adherence to production programs compared with heuristics, with benefits growing as system complexity rises.
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Feasibility of utilising waste heat from data centres for production processes requiring heat treatment: A cooperative game theory approach
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Kohei Nishiyama, Sangjic Lee, Hideyoshi Yanagisawa, Nariaki Nishino (2)
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STC O, 75/1/2026, P.
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Keywords: Heat treatment, Manufacturing system, Cooperative game theory |
Abstract : This study assesses the feasibility of utilising waste heat from co-located data centres for manufacturing heat-treatment processes. AI-driven expansion of data centres increases waste heat discharge, yet many manufacturing processes require thermal energy. We model heat demanders (manufacturers) and heat providers (data centres) as a cooperative game, where one-to-one heat-transfer matching delivers operating-cost savings. Under cost-function homogeneity, we show the game is supermodular, yielding a nonempty core and a Shapley value in it. A case study in Japan’s Inzai–Shiroi area indicates substantial value creation, with most gains accruing to manufacturers through reduced thermal energy costs.
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LLM agents-driven layout generation for reconfigurable manufacturing systems
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Tianyu Wang, Zhihao Liu, Xi Vincent Wang (2), Lihui Wang (1)
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STC O, 75/1/2026, P.
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Keywords: Large language model, Reconfiguration, Manufacturing system |
Abstract : Reconfiguration of manufacturing systems is a frequent and labor-intensive activity driven by evolving products, volumes, and operational constraints. While existing methods based on optimization, digital twins, and expert modeling provide rigorous analysis, they require explicitly specified models and substantial manual effort. This paper presents a multi-agent AI framework for generating geometry-feasible reconfigurable system layouts from updated production requirements. Leveraging 3D machine models, multiple large language model–based agents collaboratively generate and refine shopfloor layout candidates with Unity3D visualization. These high-quality solutions can be optionally optimized further using established reconfiguration
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An integrated multi-horizon approach for long-term reconfiguration and mid-term sequencing in global production networks
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Michael Martin, Vanessa Altmann / H. Weule (1)
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STC O, 75/1/2026, P.
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Keywords: Manufacturing network, Reconfiguration, Production planning |
Abstract : Rapid adaptation to volatile demand is a critical challenge for production systems in global production networks. While reconfigurable manufacturing systems enable structural adjustments of capabilities and capacities, reconfiguration activities temporarily reduce production feasibility because capabilities can be unavailable during dismantling, transportation, and installation. This paper presents an integrated multi-horizon planning approach that jointly considers long-term reconfiguration decisions and mid-term order allocation, sequencing, and replanning. Mixed-integer linear optimization models explicitly capture reconfiguration with respective dismantling, transportation, and installation processes. Computational results show that reallocating existing capabilities reduces long-term costs, while sequencing and mid-term replanning are essential to avoid backorders and improve responsiveness.
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Operational and economical performance of Equipment-as-a-Service
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Maria Chiara Magnanini (2), Tullio Tolio (1)
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STC O, 75/1/2026, P.
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Keywords: Manufacturing systems, Stochastic modelling, Circularity, Servitization. |
Abstract : Equipment-as-a-Service may become very competitive for Machine Tool Builders (MTB) which are able to regain system modules at the expiration of each contract and use them to configure new systems. The paper proposes an integrated model to evaluate operational and economical performance and to define the optimal configuration of the assembly and de-remanufacturing departments of the MTB. The model allows assessing the impact of the number of systems under EaaS and of the variability in the length of the contracts on the MTB economical performance to derive general considerations for the company strategy.
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Multi-agentic production planning utilising simulation and optimisation
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Merlin Korth, Martin Benfer, Gisela Lanza (1)
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STC O, 75/1/2026, P.
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Keywords: Artificial intelligence, Production planning, Scheduling, Large language models |
Abstract : While applications of artificial intelligence proliferate, planning complex, volatile production remains a challenge. Hybrid methods that enable large language models to interact with classic models, such as simulation and optimisation, could address this problem. This work develops a workflow-based multi-agent architecture that generates production plans from unstructured user prompts. The system is tested using data from an automotive supplier, with 7 distinct experiments in lot sizing and setup sequencing, using simulated validation. The experiments show the system can reliably create suitable production plans while reducing execution times compared to manual planning. This work presents a step towards hybrid artificial intelligence.
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LLM actor-critic based dispatching rule generation for dynamic job shop scheduling
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Marvin Carl May, Shady Salama, Johannes Pflüger, Toshiya Kaihara (1)
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STC O, 75/1/2026, P.
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Keywords: Manufacturing system, Large language model(s), Scheduling |
Abstract : Job shop scheduling is a fundamental production problem characterized by NP-hard complexity. Traditional approaches rely on numerical data processing and require significant human expertise for heuristic design. Although Large Language Models (LLMs) have demonstrated strong capabilities in processing unstructured information, their application in scheduling research has remained limited. This paper proposes an actor–critic LLM-based framework for automated dispatching rule generation. The framework combines simulation-based evaluation with two LLM components: an actor that iteratively generates dispatching rules and a critic that provides performance- and structure-based feedback. Results indicate that the proposed approach can generate competitive dispatching rules that statistically dominate state-of-the-art rules.
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A Wire Laser DED aware process planning framework with topology optimization enabled by dual-gate simulation
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Nan Yu, Jinpeng Lyu, Long Ye, Ruslan Melentiev, Stephen T. Newman (1)
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STC O, 75/1/2026, P.
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Keywords: Process planning, Simulation, Additive manufacturing |
Abstract : This paper presents a wire-laser directed energy deposition (WL-DED) aware process planning framework integrating topology optimisation with manufacturability constraints via a dual-gate simulation. The design gate verifies structural performance, while the process gate evaluates thermo-mechanical printability. Human-in-the-loop geometric reconstruction embeds WL-DED rules on feature size, overhang angle, and bead continuity. Demonstrated on an industrial gear, the workflow delivers parts’ design with over 20% lower weight and stresses and thermal distortions below 2.6 mm. The framework minimizes design–print iterations and unifies the path from optimisation to deposition-ready geometry, advancing process planning for WL-DED manufactured metal components.
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Capturing mold qualification sensitivities for adaptive startup tuning in injection molding
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Giovanni Lucchetta (2), Andrea Pieressa, Anna Bortoletto, Enrico Bovo, Nicola Milan, Marco Sorgato
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STC O, 75/1/2026, P.
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Keywords: Injection molding, Machine learning, Knowledge-based system |
Abstract : Injection-molding changeovers trigger production startups where parameters are re-tuned to recover the defect-acceptance condition, generating scrap when qualification settings are reused without adaptation. In this work, qualification is reframed as knowledge acquisition, capturing defect–parameter sensitivities for decision support. Two assistants trained on the same dataset are compared: a predictive assistant with delta-anchored tuning and a retrieval-grounded assistant reusing qualification evidence for constrained updates. Vision inspection supplies feedback. Validated on a socket cover across hydraulic and electric machines and three viscosities, the proposed assistance reduced median runs-to-quality by 88% and mean startup scrap by 94% relative to the controlled baseline.
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Human and automated demonstration data acquisition for learning repetitive industrial handling operations
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Ludger Overmeyer (2), Mirko Schaper, Phil Köhne, Justus Lübbehusen
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STC O, 75/1/2026, P.
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Keywords: Logistics, Automation, Demonstration data acquisition |
Abstract : Although automated guided vehicles with forklift functionality are increasingly deployed, most systems rely on path planning approaches with limited adaptability. At the same time, learning-based methods and regulatory requirements emphasise the demand for high-quality real-world datasets. In response to these requirements, this paper makes two main contributions: a real-world industrial truck demonstrator enabling synchronized acqui-sition of sensor and external ground-truth data, and an automated system for the generation of annotated 6D pose datasets. These advancements aim to reduce data acquisition effort while enabling accurate and verifiable datasets for industrial applications.
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An operations memory-enhanced multi-agent system for human-centric manufacturing process monitoring and decision support
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Dongpeng Li, Wenhang Dong, Yuchen Ji, Weihua Li, Pai Zheng (2), Soh Khim Ong (1)
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STC O, 75/1/2026, P.
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Keywords: Manufacturing system, Monitoring, Multi-agent system, Robotic drilling |
Abstract : Human-centric smart manufacturing requires process monitoring and decision support that remain adaptable and trustworthy under changing conditions, yet existing systems treat models, constraints, and operator interaction as loosely coupled components. This paper formulates local process monitoring and decision support as a memory-enhanced multi-agent system in which agents with distinct observability, timescales, and authority limits realize three coordinated loops: per-operation monitoring, event-triggered decision support, and memory governance. Long-horizon process knowledge is organized into episodic, semantic, and procedural memories and accessed via dual-level retrieval, where fast context-based lookup serves monitoring and deep retrieval serves decision support, while all parameter changes require operator authorization. Experiments on a robotic drilling cell show that recent episodic context improves monitoring accuracy, and memory-informed interval recommendation supports human-in-the-loop decisions with lower mean surface roughness and fewer violation-level outcomes.
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STC P |
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Task-specific systematic error evaluation of optical 3D coordinate measuring systems
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Maurizio Galetto (2), Giacomo Maculotti, Mattia Trombini, Alessandro Balsamo (1)
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STC P, 75/1/2026, P.
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Keywords: Calibration, Uncertainty, Coordinate measuring system (CMS) |
Abstract : Optical 3D Coordinate Measuring Systems (CMSs) are an effective alternative to tactile CMMs for measuring complex geometries. Uncertainty evaluation is a critical task for verifying compliance with specifications, but methods for such CMSs are missing. This work investigates the effect of workpiece geometrical characteristics on the systematic error. Results show a dependence on the workpiece characteristics that required task-specific uncertainty evaluations, and an apparent form error induced by interactions between the view direction and the workpiece geometry. Results enable artefacts’ design to improve the verification representativeness, and to model and validate requirements for digital twins to compensate for measurement errors.
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Metrological stability of multi-camera photogrammetry systems
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Edward Morse (2), Robert Schmitt (1), Jorian Khan, Matthias Bodenbonner, Yixiang Dang
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STC P, 75/1/2026, P.
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Keywords: Metrology, Motion, Calibration |
Abstract : High-speed infrared photogrammetry systems have traditionally been used in entertainment industries for motion capture. Recent work has investigated the use of these systems for large-scale dimensional metrology applications. This paper describes a methodology to quantify the stability of these systems through information obtained in the 'system calibration' process. The developed metric is applied to two laboratory motion capture systems of vastly different scales, and the subsequent experiments qualitatively relate the measurement capability of the systems to this stability metric.
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Development of an optical linear encoder with a function of calibrating scale pitch deviation
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Yuki Shimizu, Hyunsung Lim, Naoya Tashiro, Tomoki Kitazume / A. Matsubara (1)
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STC P, 75/1/2026, P.
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Keywords: Encoder, Calibration, Positioning |
Abstract : A new method is proposed and tested to realise calibration of the pitch deviation of a scale in an interferential-scanning-type optical linear encoder. An optical head is designed so that the laser beam from a displacement unit is directly used as the measuring probe in a pitch deviation unit consisting of a pair of angle sensors, and both units share the diffracted beams; this enables simultaneous detection of scale displacement and pitch deviation. The cumulative pitch deviation detected in experiments has shown a good agreement with the calibration curve of the developed linear encoder obtained by a reference laser interferometer.
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Absolute linear encoder based on a dual-periodic diffraction grating with self-referenced phase indexing
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Masaki Michihata (2), Tianyu Zhou
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STC P, 75/1/2026, P.
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Keywords: Measurement, Positioning, Grating |
Abstract : Absolute displacement measurement using diffraction grating scales is fundamentally limited by the ambiguity length. This paper proposes a grating-encoder-based displacement measurement method using a dual-periodic diffraction grating and a self-referenced phase indexing scheme for absolute position measurement. Two diffraction signals with slightly different periods are simultaneously obtained from a single track, and a composite phase is calculated from their phase difference. The individual phase values at specific composite phases serve as intrinsic indices, enabling cycle identification without additional reference marks. Experiments confirmed the expected phase behavior and demonstrated the feasibility of extending the ambiguity length to several millimeters.
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Integrated approach for function-driven metrology of lattice structures
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Filippo Zanini, Nicolò Bonato, Simone Carmignato (1)
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STC P, 75/1/2026, P.
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Keywords: Metrology, X-ray computed tomography |
Abstract : Metal additive manufacturing enables lattice structures with tailored mechanical performance, but their behaviour is highly sensitive to defects and distortions. X-ray computed tomography is the preeminent technique for non-destructive characterisation of lattice structures. However, existing metrological approaches fail to comprehensively capture the functional impact of all relevant characteristics, providing limited guidance for manufacturing process improvement. This work proposes an integrated and automated tomography-based approach for function-driven metrology of lattice structures. The framework extracts strut-level descriptors, quantifies geometric, surface, and internal defect indicators weighted by functional relevance, and aggregates them into a global criticality index. A case study validates the approach.
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A laser confocal angle sensor for surface inclination measurement
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Ryo Sato, Chen Li, Wei Gao (1)
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STC P, 75/1/2026, P.
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Keywords: Metrology, Optical, Probe |
Abstract : This paper proposes a new laser confocal angle sensor that utilizes the existing confocal configuration of laser confocal microscopy (LCM) for measurement of surface inclination angles with a focused laser light. It is verified that a differential confocal configuration, which is conventionally employed to improve the sensitivity and range of Z-position measurement in LCM, is effective to enhance the measurement accuracy of surface inclination angle. The characteristics of the proposed angle sensor are theoretically analysed by taking the parameters of confocal optics for consideration. Experiments are carried out to demonstrate the feasibility of the proposed angle sensor.
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Estimation and uncertainty assessment of TCP deflection under external loads in industrial iobots for machining applications
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Beñat Iñigo (3), June Legorburu, Markel Alaña, Gorka Aguirre, Andreas Archenti (2)
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STC P, 75/1/2026, P.
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Keywords: Calibration, Robot, Compliance |
Abstract : This work presents an automated identification procedure for robot quasistatic compliance under external loads, together with a validation framework that accounts for uncertainty. Controlled tensile forces are applied through a cable routed to a single ground-fixed pivot while TCP deflection is measured with a laser tracker, enabling scalable and largely unattended acquisition of pose–load data for parameter identification. A kinematic compliance model is then identified with practical parameter reduction, and parameter as well as input uncertainties are propagated to TCP deflection prediction intervals via Monte Carlo simulation. Validation on a MABI MAX100 robot along circular trajectories shows overall agreement with the predicted uncertainty bands, while also revealing direction-dependent effects not captured by the current model.
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Sensitivity-enhanced spin-Hall-effect ellipsometry for thin film measurement using Laguerre–Gaussian beams
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Yasuhiro Mizutani, Naila Zahra, Tsutomu Uenohara, Yasuhiro Takaya (1)
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STC P, 75/1/2026, P.
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Keywords: Surface analysis, Nano structure, Ellipsometry |
Abstract : Thin-film measurements are essential for advanced semiconductor manufacturing, requiring non-contact techniques with high-sensitivity. We previously developed an ellipsometry technique based on the spin Hall effect of light (SHEL), which is a quantum optical phenomenon that induces polarization-dependent beam position shifts upon reflection. In this study, Laguerre–Gaussian (LG) beams are employed as probe lights to enhance measurement sensitivity. LG beams of different orders are generated using a spiral phase plate and verified using interferometry. Thickness measurements of gold films thinner than 4 nm confirm that the sensitivity increases with increasing LG beam order.
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Robust full-field absolute optical thickness profiling of glass substrates combining deep learning and virtual wavelength scanning Fourier analysis
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Yangjin Kim, Hwan Kim, Toru Kizaki (2), Sung-Tae Hong (2)
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STC P, 75/1/2026, P.
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Keywords: Glass, Machine learning, Metrology |
Abstract : This study proposes a robust absolute optical thickness profiling method integrating a novel deep-learning model for precise fraction estimation with virtual wavelength scanning Fourier analysis for integer determination. Utilizing only a single fringe pattern, the proposed approach eliminates environmental sensitivity and achieves final results in less than 0.1 s, significantly outperforming conventional multi-frame phase-shifting interferometry. Its robust generalization capability was verified on three distinct glass substrates with varying thicknesses. By achieving a repeatability error of less than 3 nm, this method ensures exceptional precision and is readily applicable to high-speed, dynamic industrial inspection processes.
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A misalignment identification method based on relative ray vector observation
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Yufeng Yuan, Yueqi He, Huaming Wang, John Yin, Jianying Zhu (1)
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STC P, 75/1/2026, P.
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Keywords: Alignment, Interferometry, Relative vector |
Abstract : This paper proposes a method for identifying optical component misalignments based on relative ray vector (RRV) observation. Firstly, the RRV is calculated from the gradient direction of the wavefront. Through ray tracing, the model between the RRV and misaligned optical systems can be established. The optimization objective is to minimize the angle error between the theoretical and observed RRV. Using the error backpropagation method, the misalignment parameters of each lens surface can be optimized layer by layer. And then, calculate the lens's misalignment parameters. Simulation and experiment verified the high performance of this method in dealing with large initial misalignment.
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STC S |
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Investigation of low-cycle fatigue life of electropolished 316L stainless steel in hydrogen environment
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Sun-Ho Chang, Hyun-Taek Lee, Eun-Sang Lee / S.H. Ahn (1)
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STC S, 75/1/2026, P.
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Keywords: Electro chemical machining, Surface modification, Hydrogen embrittlement |
Abstract : Hydrogen embrittlement reduces the low‑cycle fatigue life of 316L stainless steel in hydrogen environments. This study evaluates electropolishing as a surface treatment to improve fatigue performance under electrochemical hydrogen charging. Strain‑controlled low-cycle fatigue (LCF) tests (0.8 - 1.6%) were performed on as‑received and electropolished specimens with and without hydrogen. Electropolishing reduced surface roughness, produced a Cr‑enriched passive layer, and mitigated brittle fracture and irregular striations. The fatigue life of hydrogen‑charged electropolished specimens improved by about 30% at high strain, demonstrating that electropolishing is an effective strategy to enhance hydrogen fatigue resistance.
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Solid-state-recycled aluminum profile with notable fatigue and corrosion fatigue properties made by chip extrusion
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Alexandros Prospathopoulos, Schulz Oliver, Johannes Gebhard, Yannis P. Korkolis, A. Erman Tekkaya (1), Nikolaos Michailidis (1)
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STC S, 75/1/2026, P.
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Keywords: Chip extrusion, Fatigue, Solid-state recycling |
Abstract : Solid-state recycling by hot extrusion of AA6060 machining chips avoids remelting, but fatigue-critical reliability remains uncertain. This study benchmarks T6 heat-treated tubular profiles extruded from chip-based billets against cast-billet extrusions using two extrusion parameter sets. A steady-state Eulerian FE simulation coupled to a modified Bay weld model predicts spatial weld integrity and identifies defect-prone zones, showing minimum bonding of 93.8% (Batch#1) versus 98.9% (Batch#2). Experiments confirm that higher extrusion ratio, die venting during upsetting, and lower ram speed prevent post-aging chip decohesion and enable cast-like fatigue and improved corrosion-fatigue in 3.5 wt.% NaCl. Transferable process rules are provided for industry.
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The combined effect of microstructure anisotropy and surface integrity on the fatigue resistance of AM and wrought Ti6Al4V titanium alloy
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Rachele Bertolini, Andrea Stramare, Alberto Campagnolo, Andrea Ghiotti (1), Enrico Savio (1), Stefania Bruschi (1)
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STC S, 75/1/2026, P.
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Keywords: Additive manufacturing, Machining, Fatigue |
Abstract : The paper investigates the combined effects of microstructural anisotropy and surface integrity on the fatigue performance of Ti6Al4V in wrought-equiaxed (W-E), wrought-lamellar (W-L), and laser powder bed fusion lamellar (LPBF-L) conditions under flood and cryogenic machining. Although the W-E condition shows the highest fatigue limit, it lacks the crack-deflection capability typical of lamellar microstructures. Among the lamellar states, LPBF-L exhibits greater resistance to crack propagation due to its lower anisotropy compared with W-L. Cryogenic machining improves fatigue behaviour in all conditions, with lamellar microstructures benefiting the most, as their anisotropy promotes the formation of a thicker plastically deformed layer (PDL).
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Subsurface transformations in ground Inconel 718 – obtain complementary quantitative surface integrity information through grazing-angle XRD
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Shusong Zan, Erik Abba, Dragos Axinte (1), Zhirong Liao (2)
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STC S, 75/1/2026, P.
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Keywords: Nickel alloy, Surface integrity, Phase transformation |
Abstract : While conventional electron microscopy effectively characterises machining-induced surface damage, it lacks the sensitivity to detect quantitative subsurface phase evolution, leaving a critical diagnostic gap. To address this, the present study utilises grazing-angle X-ray diffraction (GA-XRD) to provide complementary information to SEM based results. Key findings include: i) GA-XRD can create quantitative phase profiles by correlating incident angle to depth, and ii) the identification of distinct diffraction signatures can resolve diagnostic ambiguities of samples undergone different thermal load. These results demonstrate that integrating GA-XRD with microscopy is essential for a comprehensive, depth-resolved understanding of surface integrity.
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Load-independent low friction of fouling release coating in shipyard
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Seounghee Yun, Joohyun Park, Simkwan Oh, Euiseok Kong, Minsung Chun, Sanha Kim (2)
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STC S, 75/1/2026, P.
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Keywords: Coating, Friction, Surface |
Abstract : This article investigates the friction behaviour of FR coatings, focusing on the surface characteristics and the resulting real contact area formation. Contact mechanics prediction and experiments in both laboratory- and ship-scale reveal the load-independent friction characteristics, exhibiting ~0.01 of extremely low friction coefficient. The load-independent friction results from rapid contact area saturation, whereas the low friction arises from lubrication by micrometer-scale droplets released from the coating. A practical solution achieved a fivefold enhancement in friction without any damage to the coating.
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A single-experiment method for coupled transient characterization of contact heat transfer and friction in glass molding
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Thomas Bergs (2), Anh Tuan Vu, Cornelia Rojacher
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STC S, 75/1/2026, P.
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Keywords: Tribology, Glass, Inverse modeling. |
Abstract : In precision manufacturing of glass optics, friction and heat transfer at the contact interface critically influence accuracy but are difficult to quantify under transient thermo-mechanical conditions and identical surface states. This work presents a method for the simultaneous determination of friction and contact heat transfer using a pin-on-cylinder tribometer combined with infrared thermography. Transient forces and surface temperatures are synchronously measured and evaluated by inverse modelling to identify interface coefficients. The approach is validated under various conditions and demonstrates improved reliability of the measured properties. The method enables reduced experimental effort and process-relevant characterization of contact behaviour in glass molding.
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Atomic-level diamond surface fabrication by combining gas cluster ion beam amorphousization and plasma-assisted polishing
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Quanpeng He, Junkai Ren, Yongyu Fan, Yongjie Zhang, Kege Xie, Hui Deng (2)
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STC S, 75/1/2026, P.
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Keywords: Polishing, Roughness, Diamond |
Abstract : Polycrystalline diamond with atomic-level roughness is strongly required to enhance the performance of optical windows but currently suffers from subsurface damage and low polishing efficiency. Accordingly, an atomic layer polishing method that combines a gas cluster ion beam and microwave plasma is proposed for efficiently fabricating ultrasmooth and damage-free diamond surfaces. During polishing, Ar-gas cluster bombardment produces an amorphous layer to improve diamond machinability, and H2O-based plasma irradiation induces hydroxyl modification removal for atomic-level topographical formation. Thus, an ultimate surface roughness of less than 0.1 nm Sa is achieved after polishing. This work provides a new technology for ultraprecision diamond manufacturing.
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An adaptive sparse profiling and extraction of composite texture method for the mid-spatial frequency characterization of optical surfaces
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Ze Li, Chi Fai Cheung (1), Zili Zhang, Lai Ting Ho, Kin Man Lam
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STC S, 75/1/2026, P.
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Keywords: Measurement, Optical, Mid-spatial frequency |
Abstract : Mid-Spatial Frequency (MSF) errors adversely affect the performance of optical surfaces but they are difficult to be extracted via conventional surface metrology. This paper presents an adaptive sparse profiling and extraction of composite texture (ASPECT) method based on morphological component analysis, which accurately extracts MSF information of manufacturing signatures from form errors of the surface measurement data and stochastic noise. Experimental evaluation on a polished fused silica substrate demonstrates that the ASPECT method achieves a spatial consistency of approximately 73%, validating the robustness of MSF error extraction while highlighting the necessity of boundary mitigation strategies for uniform full-field characterization.
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Ultra-precision contour machining of CaF₂ cylindrical micro lens arrays
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Duo Li, Yuhu Liu, Lingwen Tan, Zelong Jia, Zhe Zhang, Mustafizur Rahman (1), Xinquan Zhang (2)
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STC S, 75/1/2026, P.
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Keywords: Ultra precision, Cylindrical micro lens arrays, Grinding, Polishing |
Abstract : In the fabrication of aspheric micro optical components, achieving both high-efficiency machining and minimized subsurface damage is considered a significant challenge. To address the machining requirements of cylindrical micro lens arrays (MLAs), a contour-based abrasive machining technique is developed in this study. The method involves contour grinding to shape the profile of MLAs, followed by contour polishing to achieve low-stress material removal. Experimental validation demonstrates that this method is able to improve surface accuracy and reduce photothermal absorption of the machined component, offering a novel approach for ultra-precision machining of micro optical components.
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Characterization of surface damage evolution in thin film composite membranes via in-situ SEM tensile testing and numerical simulations
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Fatima G. Alabtah, Abrar S. Ebrahim, Abedalkader Alkhouzaam, Brad L. Kinsey (1), Marwan K. Khraisheh (2)
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STC S, 75/1/2026, P.
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Keywords: Surface integrity, Fracture analysis, Scanning electron microscope (SEM) |
Abstract : Standard mechanical tests fail to predict the functional limits of thin-film composite (TFC) reverse osmosis (RO) membranes. This study utilizes in-situ SEM tensile testing to map real-time surface damage evolution. Results reveal a critical decoupling: functional polyamide surface cracking initiates at only 13.9% of fracture displacement, significantly preceding structural backing failure (64.3%). The failure mechanism follows a brittle channel-cracking mode, evolving from nucleation to deep strain localization. These measurable descriptors are used to calibrate a two-step finite element model, establishing a physics-based framework to predict selective-layer surface fracture, which quantitively match experiments and enhance membrane lifetime assessment.
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Chemical mechanical polishing mechanism of lutetium oxide with ceria abrasive in water: A reactive force field modelling study
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Min Lai, Boyi Sun, Guangyue Bi, Daniel Meyer (2), Fengzhou Fang (1)
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STC S, 75/1/2026, P.
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Keywords: Polishing, Modelling, Atomic and close-to-atomic scale manufacturing |
Abstract : Chemical mechanical polishing (CMP) is a key technique for achieving ultra-smooth and low-damage surfaces on brittle materials such as lutetium oxide crystals. While molecular dynamics (MD) simulations have successfully reproduced and elucidated the material removal process at the atomic level, existing models have not adequately captured the interplay between chemical and mechanical removal mechanisms. In this work, a reactive force field is developed for the lutetium oxide crystal-water–ceria abrasive system, and its reliability is validated by comparison with quantum chemical calculations and numerical studies. Using this potential, an MD model of CMP for lutetium oxide in the presence of water and ceria abrasive was first constructed, achieving atomic-scale insights into how ceria enhances the removal rate of lutetium oxide by promoting surface hydroxylation and inducing structural modifications.
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Physics-informed graph transformer for surface hardness prediction under data-limited conditions
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Dongqing Yan, Sina Malakpour Estalaki, Clayton Cooper, Robert X. Gao (1)
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STC S, 75/1/2026, P.
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Keywords: Machining, Hardness, Physics-informed machine learning |
Abstract : Hardness is a critical surface integrity metric governing the performance of machined components. Due to experimental constraints, hardness characterization typically relies on sparse measurements, limiting spatial resolution and generalization across machining conditions. This work addresses this limitation by introducing a physics-informed graph transformer for hardness prediction in milling, using process parameters and in-situ power signals. To mitigate data scarcity, power signals are synthesized, and a graph representation is constructed to embed machining physics and measurement relationships. Data analysis demonstrates robust and generalizable prediction under limited reference data, establishing a soft sensing framework for scalable characterization of hardness from milling operations.
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Process and geometry-driven pathways to in-situ surface functionalisation for enhanced heat transfer via laser powder bed fusion (LPBF)
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Michele Abruzzo, Adrian H.A. Lutey, Giuseppe Macoretta, Luca Romoli (1)
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STC S, 75/1/2026, P.
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Keywords: Additive manufacturing (AM), Texture, Boiling |
Abstract : In-situ surface functionalisation via laser powder bed fusion (LPBF) has been performed with the aim of enhancing two-phase heat transfer. Process-driven and geometry-driven approaches were developed, with the former involving partial melting of the final layer of powder and the latter production of dimple and crater arrays with controlled geometry. Values of developed area ratio greater than 110% were obtained with both strategies, achieving complete wetting with water within specific parameter ranges. Geometry-driven surfaces achieved highest convective heat transfer coefficient, up to 57% greater than machined reference surfaces, while process-driven surfaces provided robust heat transfer across a broader process window.
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Gap-synchronized laser-induced plasma machining for complex structured surface generation on sapphire
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Keyi Wu, Fang Han, Jingyuan Wang, Cao-Yang Xue, Weijian Zhang, Bing-Feng Ju, Yuelong Li, Wule Zhu (2)
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STC S, 75/1/2026, P.
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Keywords: Laser micro machining, Surface integrity, Structured surface |
Abstract : Demand for sapphire in industry is increasing, but efficiently fabricating prescribed structures remains challenging. To address this, we propose a new gap-synchronized laser-induced plasma machining method. Analysis and characterization reveal that, instead of ablation, the plasma reacts with the sapphire backside, forming a thickness-controllable deposition layer that can be removed by post polishing. Accordingly, guided by a gap–removal depth mapping relationship, the scanning path and gap distance are synchronously modulated to match the target surface, enabling precise control of removal depth. Finally, different prescribed surfaces were fabricated, demonstrating the controllable and efficient surface generation capability of the proposed method.
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