Knowledge catalogue
arXiv:2605.20644v1 Announce Type: new Abstract: Design for manufacturing plays a critical role in advanced aeroengine development, where complex components necessitate careful consideration of manufac
arXiv:2609.05559v1 Announce Type: cross Abstract: We introduce autonomous, intent-preserving Design for Manufacturing (DFM) redesign of CAD parts: given an engineer's CAD model, the method returns a v
arXiv:2605.24823v1 Announce Type: new Abstract: Manufacturing has passed through four widely recognized paradigms - mechanization, electrification, programmable automation, and Smart Manufacturing - e
arXiv:2605.25063v1 Announce Type: new Abstract: Reinforcement learning offers a promising approach for scan-order optimisation in laser additive manufacturing, where sequential scan decisions critical
arXiv:2606.01338v1 Announce Type: new Abstract: Biopharmaceutical manufacturing organizations operate under regulatory frameworks such as FDA guidance, EU Good Manufacturing Practice (GMP), and the EU
arXiv:2606.00097v1 Announce Type: new Abstract: This work presents RocketSmith, an agentic system capable of the design, manufacturing, and optimization processes in high powered rocket development. T
arXiv:2605.00839v1 Announce Type: cross Abstract: The evolution of artificial intelligence (AI) and machine learning (ML) is reshaping smart manufacturing by providing new capabilities for efficiency,
arXiv:2608.24039v1 Announce Type: cross Abstract: Manufacturing process planning transforms heterogeneous design information into coherent manufacturing decisions. However, existing approaches focus o
arXiv:2608.13233v1 Announce Type: new Abstract: Manufacturing complex soft pneumatic actuators remains challenging because geometric fidelity, compliance, structural integrity, and airtightness must b
arXiv:2605.12266v1 Announce Type: new Abstract: Graph-based machine learning has emerged as a promising approach for manufacturability analysis by learning directly from CAD models represented as Boun
arXiv:2605.03328v1 Announce Type: new Abstract: Additive manufacturing (AM) continues to transform modern manufacturing by enabling flexible, on-demand production of complex geometries across diverse
arXiv:2604.07413v1 Announce Type: new Abstract: The manufacturing sector is increasingly adopting Multimodal Large Language Models (MLLMs) to transition from simple perception to autonomous execution,
arXiv:2610.18730v1 Announce Type: new Abstract: Manufacturers often need to characterize a new material, process, or product before enough operating data are available to train reliable predictive mod
arXiv:2609.16155v1 Announce Type: cross Abstract: This paper presents a novel framework leveraging Large Language Models (LLMs) to generate synthetic time series data for manufacturing processes. Moti
arXiv:2606.10227v1 Announce Type: new Abstract: Metal additive manufacturing enables the fabrication of complex parts, but achieving consistent build quality remains challenging due to interactions in
arXiv:2603.22017v2 Announce Type: replace Abstract: This work presents a collection of multi-modal domain adapted large language models built upon the instruction tuned variants of open weight models
arXiv:2606.09892v1 Announce Type: new Abstract: Textual event records, such as alarm logs, have become an increasingly common data source in engineering and manufacturing systems. Beyond identifying c
arXiv:2605.07752v1 Announce Type: new Abstract: Semiconductor materials manufacturing presents unique challenges for machine learning deployment due to evolving process conditions, equipment degradati
arXiv:2610.06973v1 Announce Type: new Abstract: Melt-pool monitoring is central to qualifying metal additive manufacturing (AM), yet no public event-camera benchmark exists for this domain. Event came
arXiv:2610.06890v1 Announce Type: new Abstract: We present an industry experience report on three years of operating an event-driven cloud infrastructure for continuous machine learning training in au
arXiv:2609.19347v1 Announce Type: cross Abstract: Robotic additive manufacturing (AM) extends material-extrusion printing beyond gantry kinematics but makes process planning robot-dependent. A slicer-
arXiv:2608.13937v1 Announce Type: cross Abstract: Smart manufacturing processes are often installed with a large number of sensors, imaging devices and computers, which not only enable instant communi
arXiv:2605.16433v1 Announce Type: cross Abstract: Task allocation in smart manufacturing systems needs to operate under decentralized decision-making, dynamic workloads, and shared resource constraint
arXiv:2411.15361v3 Announce Type: replace Abstract: In the design of cellular manufacturing systems (CMS), numerous technological and managerial decisions must be made at both the design and operation
arXiv:2602.17679v2 Announce Type: replace Abstract: Bayesian optimization (BO) is a powerful method for optimizing black-box manufacturing processes, but its performance is often limited when dealing
arXiv:2605.17151v1 Announce Type: new Abstract: In sales and marketing, customer segmentation is an important tool for formulating strategies for customer treatment and supply chain management. Most s
arXiv:2604.28064v1 Announce Type: new Abstract: This comprehensive review examines the evolution and the current state of the art in three-dimensional (3D) reconstruction techniques in manufacturing a
arXiv:2511.17578v2 Announce Type: replace Abstract: Existing curved-layer-based process planning methods for multi-axis manufacturing address collisions only indirectly and generate toolpaths in a pos
arXiv:2609.22701v1 Announce Type: new Abstract: Manufacturing AI systems must autonomously adapt to continuous distributional shift from raw-material variability, ambient changes, and equipment aging,
arXiv:2609.22160v1 Announce Type: new Abstract: Semiconductor manufacturing relies on tightly interconnected components, so early identification of the assets most likely to fail is essential to preve
arXiv:2608.07148v1 Announce Type: new Abstract: Modern manufacturing imposes six coupled demands on adaptive control: local decisions with global consequences, partial observability, nonstationarity,
arXiv:2607.19985v1 Announce Type: new Abstract: Dynamic manufacturing environments require multi-agent systems to coordinate effectively under frequent operational disturbances such as machine failure
arXiv:2606.11605v1 Announce Type: cross Abstract: Predicting process-property relationships in manufacturing is often challenged by high experimental costs and the limited interpretability of complex
arXiv:2606.11247v1 Announce Type: cross Abstract: Generative models are increasingly used to propose designs, data, and control actions for physical systems, yet many such systems are governed by hard
arXiv:2606.07659v1 Announce Type: new Abstract: Automated surface defect detection is critical for ensuring rigorous quality control in high-speed manufacturing environments. While deep learning model
arXiv:2606.08238v1 Announce Type: new Abstract: Constitutive modeling of the relationship between process-imposed material states and fundamental material properties is critical to control of material
arXiv:2605.29144v1 Announce Type: new Abstract: Robotics Wire Arc Additive Manufacturing (WAAM) is governed by complex and nonlinear process dynamics coupling thermal field to the build geometry. The
arXiv:2604.22235v1 Announce Type: cross Abstract: Industrial robots are widely used in manufacturing, yet most manipulation still depends on fixed waypoint scripts that are brittle to environmental ch
arXiv:2604.09633v1 Announce Type: cross Abstract: This work examines how AI, especially agentic systems, is being adopted in engineering and manufacturing workflows, what value it provides today, and
arXiv:2604.09889v1 Announce Type: new Abstract: AI agents are being increasingly deployed across a wide range of real-world applications. In this paper, we propose an agentic AI framework for in-situ
arXiv:2610.09126v1 Announce Type: new Abstract: Accurate thermal modeling is essential in metal additive manufacturing (AM) for understanding the process-structure-property chain. Physics-informed neu
arXiv:2603.22118v2 Announce Type: replace Abstract: We use fused deposition modeling (FDM) 3D printing as a case study of how manufacturing robots can use imperfect AI. In FDM, print configuration str
arXiv:2610.04392v1 Announce Type: new Abstract: Existing Anomaly Detection benchmarks are saturated and often unrealistic. As part of the VAND 4.0 Challenge, we introduce a hidden-test, application-dr
arXiv:2609.09503v1 Announce Type: new Abstract: Rapid bespoke commissioning of the Cognitive Digital Twin (CDT) is a major challenge in reconfigurable manufacturing. Traditional digital twin (DT) cons
arXiv:2608.30410v1 Announce Type: cross Abstract: In semiconductor manufacturing, defect analysis is essential, but manual inspection cannot scale. However, existing automated inspection methods remai
arXiv:2608.21418v1 Announce Type: new Abstract: Manufacturing knowledge graphs that integrate data from heterogeneous industrial systems face a trust deficit: consumers cannot determine whether querie
arXiv:2608.22789v1 Announce Type: new Abstract: Additive Manufacturing (AM) plays a vital role in the ongoing industrial revolution. However, quality control remains crucial and challenging due to pri
arXiv:2608.21967v1 Announce Type: new Abstract: Automated visual inspection in manufacturing aims to replace slow and inconsistent manual checks, but its economic value depends on whether its decision
arXiv:2608.07958v1 Announce Type: new Abstract: Multimodal industrial anomaly detection has largely focused on discrete products using strongly correlated RGB and 3D observations, leaving continuous p
arXiv:2608.00369v1 Announce Type: new Abstract: This letter presents an automated robotic manufacturing system for soft capacitors which operate as actuators and sensors. Emphasis is placed on the two
arXiv:2606.29766v1 Announce Type: new Abstract: Redundant robotic multi-axis additive manufacturing (MAAM) enables support-free and conformal fabrication, but trajectory optimization for long-horizon
arXiv:2606.19358v2 Announce Type: replace Abstract: We introduceWorkBenchMark, a LEGO Duplo-based robotic assembly benchmark motivated by the RoboCup Smart Manufacturing League. Robotic assembly coupl
arXiv:2604.22857v1 Announce Type: new Abstract: This paper presents an IoT-enhanced deep learning framework for automated crack detection in Additive Manufacturing (AM) surfaces using convolutional ne
arXiv:2604.16280v1 Announce Type: new Abstract: Explaining Machine Learning (ML) results in a transparent and user-friendly manner remains a challenging task of Explainable Artificial Intelligence (XA
arXiv:2604.14562v1 Announce Type: new Abstract: Accurate thermal modeling in metal additive manufacturing (AM) is essential for understanding the process-structure-performance relationship. While prio
arXiv:2609.03761v1 Announce Type: new Abstract: This paper presents an end-to-end computational pipeline that converts a selected object mesh, a measured object state, and a selected six-axis robot in
arXiv:2509.09024v2 Announce Type: replace Abstract: The demand for lightweight and high-strength composite structures is rapidly growing in aerospace and robotics, particularly for optimized drone fra
arXiv:2608.11540v1 Announce Type: cross Abstract: The convergence of artificial intelligence (AI), Industrial Internet of Things, cyber-physical systems, and advanced robotics is reshaping manufacturi
arXiv:2606.23851v1 Announce Type: cross Abstract: This work investigates the implementation of artificial intelligence and machine learning (AI/ML) for real-time monitoring in laser powder bed fusion
arXiv:2605.12516v1 Announce Type: cross Abstract: General-purpose large language models (LLMs) often struggle to generate reliable responses in specialized engineering domains due to limited domain gr