Journal of Manufacturing Systems最新文献_第2页

Machine learning-enhanced digital twins for predictive analytics in battery pack assembly

IF 12.2 1区工程技术

Journal of Manufacturing Systems Pub Date : 2025-03-24 DOI: 10.1016/j.jmsy.2025.03.007

Muhammad Waseem , Changbai Tan , Seog-Chan Oh , Jorge Arinez , Qing Chang

引用次数: 0

A generic digital twin model construction strategy for cross-field implementations with comprehensiveness, operability and scalability

IF 12.2 1区工程技术

Journal of Manufacturing Systems Pub Date : 2025-03-24 DOI: 10.1016/j.jmsy.2025.02.020

Xiaojun Liu , Chongxin Wang , Feixiang Wang , Xiaoli Qiu , Fengyi Feng , Yang Sun

{"title":"A generic digital twin model construction strategy for cross-field implementations with comprehensiveness, operability and scalability","authors":"Xiaojun Liu , Chongxin Wang , Feixiang Wang , Xiaoli Qiu , Fengyi Feng , Yang Sun","doi":"10.1016/j.jmsy.2025.02.020","DOIUrl":"10.1016/j.jmsy.2025.02.020","url":null,"abstract":"<div><div>In recent years, the prominence of Digital Twins as pivotal tools in digitization and intelligence has sparked widespread interest. However, the diversity of Digital Twin applications has led to a plethora of evolving technologies, standards, and building methods. These varying terms and frequent incompatibilities necessitate a unified approach to characterize and craft Digital Twin models. This endeavor aims not only to streamline construction processes but also to ensure the reusability and collaboration of Digital Twin models across diverse scenarios. This work proposes Digital twin model building strategy (DTBS), deriving four key processes for constructing digital twin models from the perspective of application scenarios: based on physical entities, twin service requirements, physical data, and entity requirements. Subsequently, by defining the application scenarios and employing suitable strategies, the building of digital twin models is accomplished. The DTBS serves as the core strategy for the building of digital twin models, guiding the complete construction process of digital twin models. The DTBS aims to achieve three objectives: comprehensiveness (encompassing all stages of digital twin model building), operability (with low thresholds for researchers and practitioners), and scalability (encompassing not just one scenario, but multiple domains). Additionally, through case studies, the effectiveness of the Digital twin model building strategy in practical engineering contexts is expounded upon. This strategy's strength lies in its ability to maintain scalability while also demonstrating comprehensiveness and operability.</div></div>","PeriodicalId":16227,"journal":{"name":"Journal of Manufacturing Systems","volume":"80 ","pages":"Pages 366-379"},"PeriodicalIF":12.2,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143683290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Life cycle assessment and energy characterization of friction surfacing deposition of aluminum alloys

IF 12.2 1区工程技术

Journal of Manufacturing Systems Pub Date : 2025-03-24 DOI: 10.1016/j.jmsy.2025.03.008

Simone Amantia , Kirill Kalashnikov , Gianni Campatelli , Livan Fratini , Giuseppe Ingarao

{"title":"Life cycle assessment and energy characterization of friction surfacing deposition of aluminum alloys","authors":"Simone Amantia , Kirill Kalashnikov , Gianni Campatelli , Livan Fratini , Giuseppe Ingarao","doi":"10.1016/j.jmsy.2025.03.008","DOIUrl":"10.1016/j.jmsy.2025.03.008","url":null,"abstract":"<div><div>In this work, an experimental investigation of Friction Surfacing Deposition (FSD) using the 2000-series heat-treatable aluminum alloy was performed including the environmental impact characterization of the process. The effect of main controlling process parameters and their interactions on energy demand during the single layer deposition was evaluated. A full Life Cycle Assessment (LCA) analysis was conducted for layer-by-layer deposition and a comparison of FSD with the Cold Metal Transfer Wire Arc Additive Manufacturing (WAAM) was performed for a specific wall-shaped sample production. It was observed that the FSD process is characterized by lower processing energy than WAAM, but also by a much higher amount of material scrap connected to undeposited parts of consumable tools such as a flash. To assess the possibility of reducing the material waste during FSD, the comparative LCA analysis was expanded to study the impact of the deposited layer length. It was shown that the FSD method can be a more environmentally friendly process when the deposition of at least 450-mm-long layer using a unique tool is required.</div></div>","PeriodicalId":16227,"journal":{"name":"Journal of Manufacturing Systems","volume":"80 ","pages":"Pages 356-365"},"PeriodicalIF":12.2,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143683289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multi-objective collaborative optimization of green disassembly planning and recovery option decision considering the learning effect

IF 12.2 1区工程技术

Journal of Manufacturing Systems Pub Date : 2025-03-24 DOI: 10.1016/j.jmsy.2025.03.011

Yibing Li , Wenxia Zhu , Jun Guo , Kaipu Wang , Liang Gao

{"title":"Multi-objective collaborative optimization of green disassembly planning and recovery option decision considering the learning effect","authors":"Yibing Li , Wenxia Zhu , Jun Guo , Kaipu Wang , Liang Gao","doi":"10.1016/j.jmsy.2025.03.011","DOIUrl":"10.1016/j.jmsy.2025.03.011","url":null,"abstract":"<div><div>With the continuous improvement of environmental awareness, the recovery of end-of-life products has received widespread attention. Rational decision-making on the recovery options of product parts is an effective way to achieve environmental goals. Meanwhile, manual disassembly is very important in the recycling process, and the learning effect of workers has a great influence on disassembly. Therefore, a collaborative selective disassembly planning and end-of-life products recovery option decision model considering the learning effect is proposed. The objective is to minimize disassembly time, and carbon emissions and maximize disassembly profit. To obtain a high-quality disassembly scheme, an improved multi-objective genetic algorithm based on Q-learning is proposed. To improve the quality of the initial solution, a three-layer encoding strategy including disassembly sequence, disassembly decision sequence, and recovery option decision sequence is designed. Four search strategies are designed as actions for Q-learning, and the state is constructed based on population fitness. This way can enable the algorithm to dynamically adjust the optimization search strategy during the iterative process. Then, the accuracy and effectiveness of the algorithm are verified by two test cases. Next, the proposed model and algorithm are applied to a real refrigerator disassembly case. The results show that due to the learning effect, the efficiency of the disassembly can be increased by 31.66 %, the cost can be reduced by 30.44 %, and the carbon emissions can be reduced by 30.07 %. In addition, carbon emissions can be reduced by 34.82 % by co-optimizing disassembly planning and recovery option decisions.</div></div>","PeriodicalId":16227,"journal":{"name":"Journal of Manufacturing Systems","volume":"80 ","pages":"Pages 324-343"},"PeriodicalIF":12.2,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143683287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Task allocation and scheduling to enhance human–robot collaboration in production line by synergizing efficiency and fatigue

IF 12.2 1区工程技术

Journal of Manufacturing Systems Pub Date : 2025-03-22 DOI: 10.1016/j.jmsy.2025.03.006

Fan Zeng , Changxiang Fan , Shouhei Shirafuji , Yusheng Wang , Masahiro Nishio , Jun Ota

{"title":"Task allocation and scheduling to enhance human–robot collaboration in production line by synergizing efficiency and fatigue","authors":"Fan Zeng , Changxiang Fan , Shouhei Shirafuji , Yusheng Wang , Masahiro Nishio , Jun Ota","doi":"10.1016/j.jmsy.2025.03.006","DOIUrl":"10.1016/j.jmsy.2025.03.006","url":null,"abstract":"<div><div>Introducing robots to assist humans in production lines can reduce human fatigue, but efficiency should also not be overlooked. Therefore, task allocation and scheduling, which determine who performs tasks and when they start and finish, should consider both efficiency and fatigue in human–robot collaboration. Efficiency needs to be maximized while fatigue needs to be minimized, necessitating a compromise solution to balance these conflicting objectives. Task allocation guided by multiple objectives is computationally more complex. Furthermore, the production line, with its numerous components and tasks, typically has a larger search space, especially in scenarios involving multiple humans and robots. This complexity makes it challenging for most current human–robot task allocation methods to effectively address such problems. Thus, a new task allocation and scheduling method to balance efficiency and fatigue is proposed in this paper. It reallocates initial sequential human actions to all the humans and robots, obtains locally optimal solutions by multi-heuristics search with efficiency and fatigue synergized, and a fast-converging greedy search is then employed to refine these locally optimal solutions to approach the global optimum. What is more, the proposed method was applied to a laboratory-constructed production line and extended to more complex scenarios involving four different setups, as well as the scalability experiment, demonstrating superior task allocation and scheduling capabilities in balancing the efficiency and fatigue of complex scenarios.</div></div>","PeriodicalId":16227,"journal":{"name":"Journal of Manufacturing Systems","volume":"80 ","pages":"Pages 309-323"},"PeriodicalIF":12.2,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143683173","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

CAM as a Service with dynamic toolpath generation ability for process optimization in STEP-NC compliant CNC machining

IF 12.2 1区工程技术

Journal of Manufacturing Systems Pub Date : 2025-03-21 DOI: 10.1016/j.jmsy.2025.03.004

Kaiyao Zhang, Wenlei Xiao, Xiangming Fan, Gang Zhao

{"title":"CAM as a Service with dynamic toolpath generation ability for process optimization in STEP-NC compliant CNC machining","authors":"Kaiyao Zhang, Wenlei Xiao, Xiangming Fan, Gang Zhao","doi":"10.1016/j.jmsy.2025.03.004","DOIUrl":"10.1016/j.jmsy.2025.03.004","url":null,"abstract":"<div><div>The next generation of STEP-NC technology needs to achieve more intelligent process optimization. Currently, the calculation method of toolpath length in process optimization algorithms hinders the flexibility and adaptability of algorithm applications. Process optimization needs to generate toolpath based on dynamic process parameter combinations automatically. To address this issue, this paper deploys CAM on the cloud based on the STEP-NC edge-cloud collaboration system, enabling the automatic generation of toolpath through interaction with the process parameter optimization process. Building on this, a non-dominated sorting genetic algorithm III with CAM as a service (NSGAIII-CaaS) for process optimization is proposed. Additionally, a process optimization method for machining feature elements is introduced. Finally, the proposed method is applied to optimize process parameters for three features of a typical part from COMAC, targeting machining cost and machining time. The feasibility of the proposed method’s application in manufacturing enterprises is verified. Using the optimized process parameters for machining features, the cost is reduced by over 70%, efficiency is improved by 70%, and redundant toolpath in machining features are optimized.</div></div>","PeriodicalId":16227,"journal":{"name":"Journal of Manufacturing Systems","volume":"80 ","pages":"Pages 294-308"},"PeriodicalIF":12.2,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143683140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Designing worker assistance systems–Methodology development and industrial validation

IF 12.2 1区工程技术

Journal of Manufacturing Systems Pub Date : 2025-03-19 DOI: 10.1016/j.jmsy.2025.02.022

Patrick Bründl , Christina Wegener , Micha Stoidner , Johannes Bayer , Benedikt Scheffler , Huong Giang Nguyen , Jörg Franke

{"title":"Designing worker assistance systems–Methodology development and industrial validation","authors":"Patrick Bründl , Christina Wegener , Micha Stoidner , Johannes Bayer , Benedikt Scheffler , Huong Giang Nguyen , Jörg Franke","doi":"10.1016/j.jmsy.2025.02.022","DOIUrl":"10.1016/j.jmsy.2025.02.022","url":null,"abstract":"<div><div>This research paper presents a comprehensive methodology for the design and implementation of worker assistance systems, with a focus on enhancing technology acceptance in industrial settings. A systematic literature review was conducted to analyze existing approaches, identify gaps, and define requirements for the methodology. The proposed methodology TERA-AS (Tasks, Environment, Relevance, Acceptance of Assistance Systems) begins with a detailed analysis of the initial working environment, capturing physical strain, task complexity, and job-specific conditions using a structured questionnaire and guidelines. A catalog of necessary assistance functions is then derived, and a system matrix matches these needs to 16 different assistance systems, facilitating the selection of an optimal solution based on a cost-benefit analysis. TERA-AS emphasizes employee involvement in system design and clear communication throughout the implementation process to foster technology acceptance. Therefore, this approach not only focuses on creating technologically and economically viable assistance functions, but also ensures technology acceptance. It was applied in a real-world industrial use case, specifically in control cabinet manufacturing. The tested system was a laser projection optical assistance system based on AI-generated positional data. Evaluation of the system showed significant time savings for manual assembly processes —approximately 69.05 % in wiring and 26.04 % in electrical assembly—despite involving untrained personnel. Feedback from operators highlighted both the system's effectiveness and areas for improvement, such as material provision and user interface design. Overall, TERA-AS provides a structured methodology to digital worker assistance system implementation, ensuring successful adoption through early employee engagement and continuous system improvement.</div></div>","PeriodicalId":16227,"journal":{"name":"Journal of Manufacturing Systems","volume":"80 ","pages":"Pages 272-293"},"PeriodicalIF":12.2,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143654550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

MaViLa: Unlocking new potentials in smart manufacturing through vision language models

IF 12.2 1区工程技术

Journal of Manufacturing Systems Pub Date : 2025-03-18 DOI: 10.1016/j.jmsy.2025.02.017

Haolin Fan , Chenshu Liu , Neville Elieh Janvisloo , Shijie Bian , Jerry Ying Hsi Fuh , Wen Feng Lu , Bingbing Li

{"title":"MaViLa: Unlocking new potentials in smart manufacturing through vision language models","authors":"Haolin Fan , Chenshu Liu , Neville Elieh Janvisloo , Shijie Bian , Jerry Ying Hsi Fuh , Wen Feng Lu , Bingbing Li","doi":"10.1016/j.jmsy.2025.02.017","DOIUrl":"10.1016/j.jmsy.2025.02.017","url":null,"abstract":"<div><div>In smart manufacturing, there remains a gap in the system-level understanding of manufacturing processes that hinders the effective integration of artificial intelligence (AI) for autonomous planning and execution in dynamic real-world scenarios. This paper presents MaViLa, an advanced vision language model (VLM) specifically designed for the smart manufacturing domain. MaViLa enhances visual understanding in the manufacturing domain through two key approaches: first, it uses a retrieval augmented generation (RAG) pipeline to incorporate domain knowledge during dataset creation, and second, it implements a robust two-stage training paradigm of pre-training followed by instruction fine-tuning. Comparative evaluations of domain-relevant benchmarks demonstrate MaViLa’s superior performance over general-purpose VLMs, particularly in manufacturing-specific tasks such as process optimization and quality control. Experimental results, including laboratory tests and in-situ monitoring applications, highlight the effectiveness of MaViLa in scene understanding and decision-making support. With its scalability and seamless integration of external tools, MaViLa paves the way for more efficient human–machine interactions and the development of autonomous, holistic manufacturing systems. These advancements establish MaViLa as a key technology that unlocks new potential for smart manufacturing.</div></div>","PeriodicalId":16227,"journal":{"name":"Journal of Manufacturing Systems","volume":"80 ","pages":"Pages 258-271"},"PeriodicalIF":12.2,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143654738","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Sensor placement utilizing a digital twin for thermal error compensation of machine tools

IF 12.2 1区工程技术

Journal of Manufacturing Systems Pub Date : 2025-03-17 DOI: 10.1016/j.jmsy.2025.03.003

Sebastian Lang , Mario Zorzini , Stephan Scholze , Josef Mayr , Markus Bambach

{"title":"Sensor placement utilizing a digital twin for thermal error compensation of machine tools","authors":"Sebastian Lang , Mario Zorzini , Stephan Scholze , Josef Mayr , Markus Bambach","doi":"10.1016/j.jmsy.2025.03.003","DOIUrl":"10.1016/j.jmsy.2025.03.003","url":null,"abstract":"<div><div>Thermal errors in machine tools significantly impact precision and, therefore, productivity. Mitigating these errors often results in a trade-off between energy efficiency and accuracy. While data-driven compensation models show promise in addressing this challenge and achieving sustainable precision, their effectiveness hinges on the careful selection and placement of sensors as model inputs. This paper introduces a novel temperature sensor positioning method for thermal error compensation that leverages a digital twin framework to virtually determine ideal sensor positions and their effects on the compensation model. By accurately identifying temperature-sensitive points, our approach improves compensation accuracy and reduces the number of sensors required, thus enhancing both model robustness and operational efficiency. For choosing this set not only one simulation model is used but an ensemble with varying boundary conditions and thus model properties. Validation results show that the proposed method outperforms traditional, manually determined sensor placement strategies, providing a scalable solution for adaptable, energy-efficient thermal management in precision manufacturing. The selected sensor set based on a hybrid singular value decomposition and Least Absolute Shrinkage and Selection Operator approach yields a more robust compensation using only 7 instead of the manually chosen 22 temperature sensors. The thermal error reduction ranges from 77%–94% using simulated data with a corresponding reduction of 75%–85% achieved on the physical machine.</div></div>","PeriodicalId":16227,"journal":{"name":"Journal of Manufacturing Systems","volume":"80 ","pages":"Pages 243-257"},"PeriodicalIF":12.2,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143637558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Meta-knowledge triple driven multi-modal knowledge graph construction method and application in production line control with Gantt charts

IF 12.2 1区工程技术

Journal of Manufacturing Systems Pub Date : 2025-03-13 DOI: 10.1016/j.jmsy.2025.03.002

Laiyi Li, Maolin Yang, Inno Lorren Désir Makanda, Pingyu Jiang

{"title":"Meta-knowledge triple driven multi-modal knowledge graph construction method and application in production line control with Gantt charts","authors":"Laiyi Li, Maolin Yang, Inno Lorren Désir Makanda, Pingyu Jiang","doi":"10.1016/j.jmsy.2025.03.002","DOIUrl":"10.1016/j.jmsy.2025.03.002","url":null,"abstract":"<div><div>Digital manufacturing involves complex and multidimensional interactions among production line resources, resulting in massive multi-modal knowledge. The knowledge often lacks correlation and contextual readability, leading to data silos. The rapid development of knowledge graphs (KGs) has rekindled interest in manufacturing knowledge engineering. Investigating the framework of multi-modal manufacturing data assets in enterprises and transforming them into a general-purpose KG database to support manufacturing processes is of significant importance. Guided by the principle of using KG as a manufacturing database, this study developed a multi-modal production line manufacturing knowledge graph (PLMKG) to support dynamic manufacturing on production lines. Firstly, the schema layer of the PLMKG is constructed using the Entity-Relationship model and a manufacturing knowledge pattern framework, with meta-knowledge triples proposed for schema data expression. Secondly, an event-state trigger dynamic instantiation method based on triples binding is proposed to enable self-growth. Third, a method integrating dynamic Gantt charts is introduced to synchronize the control of PLMKG and the manufacturing process. The anomaly detection model is employed to detect production, with the results stored in the PLMKG and Gantt charts for process control. Finally, a PLMKG prototype system for data management and process visualization is developed, with a 3D printing production line case study validating the construction and application of PLMKG. The results indicate that the proposed PLMKG integrates multi-modal manufacturing knowledge structurally and provides AI readiness for manufacturing, finally supporting the production line operation as a database.</div></div>","PeriodicalId":16227,"journal":{"name":"Journal of Manufacturing Systems","volume":"80 ","pages":"Pages 224-242"},"PeriodicalIF":12.2,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143621440","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0