Journal of Manufacturing Systems最新文献_第6页

AI-enhanced digital twins in maintenance: Systematic review, industrial challenges, and bridging research–practice gaps 维护中的人工智能增强数字孪生：系统审查、行业挑战和弥合研究实践差距

IF 14.2 1区工程技术

Journal of Manufacturing Systems Pub Date : 2025-07-29 DOI: 10.1016/j.jmsy.2025.07.006

Siyuan Chen, Ebru Turanoglu Bekar, Jon Bokrantz, Anders Skoogh

{"title":"AI-enhanced digital twins in maintenance: Systematic review, industrial challenges, and bridging research–practice gaps","authors":"Siyuan Chen, Ebru Turanoglu Bekar, Jon Bokrantz, Anders Skoogh","doi":"10.1016/j.jmsy.2025.07.006","DOIUrl":"10.1016/j.jmsy.2025.07.006","url":null,"abstract":"<div><div>The convergence of artificial intelligence (AI) and digital twin technology is reshaping maintenance strategies in the era of Industry 4.0. However, gaps persist between academic advancements and industrial adoption and expectation. This study systematically investigates the landscape of AI-enhanced digital twins for maintenance by integrating a systematic literature review (SLR) of related studies with in-depth interviews from industry practitioners. Our analysis reveals that while academia demonstrates robust applications of supervised, deep, and reinforcement learning to optimize digital twin models and prescribe data-driven actions, industrial implementation remains limited by challenges such as high scale dimension, data integration complexities, and insufficient workforce readiness. We identified and articulated three critical gap dimensions, scale, data, and model between academic research and industrial implementation and expectation. To bridge these gaps, we proposed a comprehensive five-layer framework for AI-enhanced digital twins, encompassing physical assets, data transmission, digital twins, AI analytics, and maintenance services. Actionable recommendations are provided, including the adoption of modular architectures, standardized data protocols, hybrid edge-cloud solutions, and targeted workforce upskilling. Our findings not only clarify the current state and challenges of AI-driven digital twins in maintenance but also offer a practical roadmap for accelerating their industrial implementation. This work advances the field by integrating insights from both academic research and industrial practice, offering concrete recommendations to support the practical realization of smart and sustainable maintenance practices.</div></div>","PeriodicalId":16227,"journal":{"name":"Journal of Manufacturing Systems","volume":"82 ","pages":"Pages 678-699"},"PeriodicalIF":14.2,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144721956","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

A digital twin shop-floor construction method towards seamless and resilient control 一种面向无缝弹性控制的数字化双车间施工方法

IF 12.2 1区工程技术

Journal of Manufacturing Systems Pub Date : 2025-07-24 DOI: 10.1016/j.jmsy.2025.07.017

Chenyuan Zhang , Fei Tao , Weiran Liu , Ying Cheng , Lihui Wang

{"title":"A digital twin shop-floor construction method towards seamless and resilient control","authors":"Chenyuan Zhang , Fei Tao , Weiran Liu , Ying Cheng , Lihui Wang","doi":"10.1016/j.jmsy.2025.07.017","DOIUrl":"10.1016/j.jmsy.2025.07.017","url":null,"abstract":"<div><div>In recent years, as a promising way to realize smart manufacturing, digital twin shop-floor has attracted more and more attentions. Frontier researches have preliminarily shown that the interaction, which is the core feature of digital twin, is beneficial for dynamic analysis, real-time production management and remote shop-floor control. However, current research pays scant attention to the seamless control under uncertain conditions, which could lead to outdated or ineffective control because of the interaction delay and uncertainty. To address this problem, this paper firstly proposed a digital twin shop-floor construction framework towards seamless control under uncertain conditions. Moreover, connotations of seamless and resilient control are also introduced. Then, the Lego-style modeling and configuring method of digital twin shop-floor are discussed, to provide the basis for digital twin shop-floor development and seamless control. Predictive interaction mechanism for resilient control is further explained in detail. Finally, a digital twin shop-floor for chemical fiber production is chosen as the case to validate the effectiveness and feasibility of proposed framework and method.</div></div>","PeriodicalId":16227,"journal":{"name":"Journal of Manufacturing Systems","volume":"82 ","pages":"Pages 660-677"},"PeriodicalIF":12.2,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144702988","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

Mixed-model and multi-model assembly lines: A systematic literature review on resource management 混合模型和多模型装配线：资源管理的系统文献综述

IF 12.2 1区工程技术

Journal of Manufacturing Systems Pub Date : 2025-07-24 DOI: 10.1016/j.jmsy.2025.07.005

Mattia Gianassi , Leonardo Leoni , Italo Cesidio Fantozzi , Filippo De Carlo , Mario Tucci

{"title":"Mixed-model and multi-model assembly lines: A systematic literature review on resource management","authors":"Mattia Gianassi , Leonardo Leoni , Italo Cesidio Fantozzi , Filippo De Carlo , Mario Tucci","doi":"10.1016/j.jmsy.2025.07.005","DOIUrl":"10.1016/j.jmsy.2025.07.005","url":null,"abstract":"<div><div>In modern dynamic manufacturing context, product personalisation, and the production-line customisation it may require, are crucial sources of competitiveness, making mixed-model and multi-model assembly lines indispensable. The variability resulting from both internal and external factors, along with resource flexibility, plays a critical role in these settings. Nonetheless, systematic analyses of how resources are considered in such environments remain limited, particularly about variability and the interactions among different resource types. Thus, this work conducts a Systematic Literature Review, analysing 63 studies on Mixed-Model Assembly Lines (MMALPs) and Multi-Model Assembly Lines (MuMALPs). The review investigates resource characteristics – such as space, operator skills, costs, or equipment availability – and whether and how variability in operating times or market demand is addressed. The review shows that cost and availability are the most frequently examined resource characteristics, while space remains comparatively underexplored. Line design and line balancing stand out as the primary objectives, typically tackled via integer programming or metaheuristics, whereas machine learning – though less common overall – is more often employed under high-variability conditions. The results offer practical insights for both researchers and practitioners by highlighting the current gaps uncovered by these findings and suggesting avenues that would be particularly valuable to explore in light of the results obtained, thereby underscoring the need for more in-depth research on flexible and reconfigurable lines, as well as broader implementation in real-world applications in MMALPs and MuMALPs.</div></div>","PeriodicalId":16227,"journal":{"name":"Journal of Manufacturing Systems","volume":"82 ","pages":"Pages 632-657"},"PeriodicalIF":12.2,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144695254","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

Integrating life cycle engineering into design for additive manufacturing: A review 将生命周期工程集成到增材制造设计中：综述

IF 12.2 1区工程技术

Journal of Manufacturing Systems Pub Date : 2025-07-24 DOI: 10.1016/j.jmsy.2025.07.010

Claudio Favi , Luca Murgese , Nicola Villazzi , Simone Gallozzi , Marco Mandolini , Marco Marconi

{"title":"Integrating life cycle engineering into design for additive manufacturing: A review","authors":"Claudio Favi , Luca Murgese , Nicola Villazzi , Simone Gallozzi , Marco Mandolini , Marco Marconi","doi":"10.1016/j.jmsy.2025.07.010","DOIUrl":"10.1016/j.jmsy.2025.07.010","url":null,"abstract":"<div><div>Life cycle engineering is a crucial design methodology to support optimized design choices in the context of ecodesign, particularly for components manufactured with novel technologies such as additive manufacturing. This study presents a systematic literature review on the topic, analysing 87 publications following the PRISMA framework. The review explores the environmental and economic life cycle implications of additive manufacturing in relation to the technological features and engineering design aspects. Additionally, it shows existing frameworks for integrating ecodesign into sustainability assessments of additive manufacturing and the development of ecodesign guidelines. From an engineering perspective, these technologies introduce several advantages enabling the creation of lightweight, multi-functional, and performance-optimized components. However, challenges related to high energy consumption, material preparation, and variability in life cycle impacts need to be addressed with dedicated life cycle analysis to ensure environmental and economic sustainability. Existing methods for integrating ecodesign into life cycle assessment are fragmented, with limited frameworks combining environmental and economic aspects. Emerging approaches, such as automated life cycle assessment tools, show promise but remain underexplored. Ecodesign guidelines emphasize well-known strategies such as material optimization and waste reduction. Nonetheless, translating these guidelines into standardized practices remains a challenge. This review highlights the need for comprehensive and standardized life cycle engineering frameworks to guide sustainable design decisions throughout all product life cycle phases, ensuring that additive manufacturing technologies fulfil their potential as enablers of environmentally and economically sustainable manufacturing.</div></div>","PeriodicalId":16227,"journal":{"name":"Journal of Manufacturing Systems","volume":"82 ","pages":"Pages 599-631"},"PeriodicalIF":12.2,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144695253","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

Advances in design and quality improvement for cyber manufacturing 网络制造的设计和质量改进进展

IF 12.2 1区工程技术

Journal of Manufacturing Systems Pub Date : 2025-07-24 DOI: 10.1016/j.jmsy.2025.07.007

Chenang Liu, Xiaoyu Chen, Marco Grasso

引用次数: 0

Diffusion model-driven smart design and manufacturing: Prospects and challenges 扩散模型驱动的智能设计与制造：前景与挑战

IF 12.2 1区工程技术

Journal of Manufacturing Systems Pub Date : 2025-07-22 DOI: 10.1016/j.jmsy.2025.07.011

Jiewu Leng , Xuyang Su , Zean Liu , Lianhong Zhou , Chong Chen , Xin Guo , Yiwei Wang , Ru Wang , Chao Zhang , Qiang Liu , Xin Chen , Weiming Shen , Lihui Wang

{"title":"Diffusion model-driven smart design and manufacturing: Prospects and challenges","authors":"Jiewu Leng , Xuyang Su , Zean Liu , Lianhong Zhou , Chong Chen , Xin Guo , Yiwei Wang , Ru Wang , Chao Zhang , Qiang Liu , Xin Chen , Weiming Shen , Lihui Wang","doi":"10.1016/j.jmsy.2025.07.011","DOIUrl":"10.1016/j.jmsy.2025.07.011","url":null,"abstract":"<div><div>Artificial Intelligence-Generated Content (AIGC), particularly diffusion models as a key component of Generative Artificial Intelligence (GenAI), are transforming smart design and manufacturing in the interplay of Industry 4.0 and Industry 5.0. This paper analyzes the applications of diffusion models in smart design and manufacturing, focusing on three key pillars: diffusion-driven generative design, smart control, and fault diagnosis. Diffusion models enhance manufacturing system flexibility, resilience, and sustainability through their applications as generative design engines, intelligent controllers for adaptive manufacturing processes, and predictive tools for fault diagnosis. This study provides a comprehensive review of the current state of diffusion model-driven smart design and manufacturing. It analyzes key challenges such as model efficiency, data dependency, and system integration, while providing a constructive perspective on potential solutions. This paper also integrates Industry 5.0 considerations by connecting the applications and technical solutions to the core values of human-centricity, sustainability, and resilience. It concludes by emphasizing the necessity of continuous refinement of diffusion models and interdisciplinary research to integrate them into smart design and manufacturing systems further, fostering a more human-centric, resilient, and sustainable industry.</div></div>","PeriodicalId":16227,"journal":{"name":"Journal of Manufacturing Systems","volume":"82 ","pages":"Pages 561-577"},"PeriodicalIF":12.2,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144679338","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

RMDTs: Process-oriented function-triggered robotic milling digital twin system for service-expansion rmdt：面向过程的功能触发机器人铣削数字孪生系统，用于服务扩展

IF 12.2 1区工程技术

Journal of Manufacturing Systems Pub Date : 2025-07-22 DOI: 10.1016/j.jmsy.2025.07.015

Shengqiang Zhao , Fangyu Peng , Yunan Shan , Juntong Su , Xiaowei Tang , Rong Yan

{"title":"RMDTs: Process-oriented function-triggered robotic milling digital twin system for service-expansion","authors":"Shengqiang Zhao , Fangyu Peng , Yunan Shan , Juntong Su , Xiaowei Tang , Rong Yan","doi":"10.1016/j.jmsy.2025.07.015","DOIUrl":"10.1016/j.jmsy.2025.07.015","url":null,"abstract":"<div><div>Recently, with the rapid development of information sensing and artificial intelligence, there exists a giant demand for high-performance machining of large complex components, especially for milling robot with both heavy-loaded cutting ability and flexible posture under extreme constraints. For both digital twin and robotic intelligent manufacturing, it has a broadly interdisciplinary prospect around the frontier basic science including sensing, data, information and AI. However, there exists a lacking of academic research and engineering exploration on the theory framework, function module, and service application of digital twin systems in robotic manufacturing. In this paper, a robotic milling digital twin system (RMDTs) based on process orientation, function triggering, and service extension is innovatively proposed. Furthermore, a dual-loop framework of RMDTs is established. The predictive simulation foreknowledge and intelligent decision-making are introduced, which enriches the outer loop of RMDTs. Furthermore, process data and its flow form of robotic milling is developed to construct the function modules of digital twin system. Finally, the proposed RMDTs has been validated in service expansion of three typical cases, with the excellent performance on motion performance and machining quality of robotic milling. The proposed framework and function modules of RMDTs display the potential to break through the extremely constrained conditions and flexible machining technology in robotic milling, supporting to develop the intelligent set of large-sized robotic machining equipment on the complicated curved marine propellers.</div></div>","PeriodicalId":16227,"journal":{"name":"Journal of Manufacturing Systems","volume":"82 ","pages":"Pages 578-598"},"PeriodicalIF":12.2,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144687287","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

A method for considering aleatory and epistemic uncertainties as well as product variance in discrete event simulation of production systems 一种考虑生产系统离散事件仿真中随机不确定性和认知不确定性以及产品方差的方法

IF 12.2 1区工程技术

Journal of Manufacturing Systems Pub Date : 2025-07-22 DOI: 10.1016/j.jmsy.2025.06.007

Alex Maximilian Frey , Tristan Maul , Rick Hörsting , Jan Stindt , Marvin Carl May , Peter Mark , Gisela Lanza

{"title":"A method for considering aleatory and epistemic uncertainties as well as product variance in discrete event simulation of production systems","authors":"Alex Maximilian Frey , Tristan Maul , Rick Hörsting , Jan Stindt , Marvin Carl May , Peter Mark , Gisela Lanza","doi":"10.1016/j.jmsy.2025.06.007","DOIUrl":"10.1016/j.jmsy.2025.06.007","url":null,"abstract":"<div><div>When modelling a production system during its planning phase, aleatory uncertainties of production processes, epistemic uncertainties resulting from insufficient knowledge as well as variations in the production processes resulting from product variances must be considered. These different uncertainties and variances are interrelated, e.g. the influence of product variants on production processes may itself be subject to epistemic uncertainty. This paper presents a generic method to model aleatory and epistemic uncertainties in discrete event simulations of production systems as well as product variances in an integrated manner. We use functional relations between product parameters and production model parameters to efficiently account for product variances. We use possibility-probability transformation and second-order Monte Carlo simulation to account for epistemic uncertainty. For easy transferability to industrial practice, a step-by-step procedure is described that can be implemented in commercially available simulation tools. A use case from precast concrete production is presented to show the benefit of such an approach compared to a state-of-the-art benchmark.</div></div>","PeriodicalId":16227,"journal":{"name":"Journal of Manufacturing Systems","volume":"82 ","pages":"Pages 547-560"},"PeriodicalIF":12.2,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144679337","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

IF 12.2 1区工程技术

Journal of Manufacturing Systems Pub Date : 2025-07-19 DOI: 10.1016/j.jmsy.2025.07.003

Qinglin Gao , Jianhua Liu , Shimin Liu , Cunbo Zhuang

{"title":"From human-related to human-centric: A review of shop floor scheduling problem under Industry 5.0","authors":"Qinglin Gao , Jianhua Liu , Shimin Liu , Cunbo Zhuang","doi":"10.1016/j.jmsy.2025.07.003","DOIUrl":"10.1016/j.jmsy.2025.07.003","url":null,"abstract":"<div><div>The emergence of Industry 5.0 marks a paradigmatic shift in manufacturing, emphasizing human-centricity, sustainability, and resilience. This transformation redefines the central role of humans within industrial ecosystems. As a key enabler of intelligent manufacturing, shop floor scheduling plays a pivotal role in optimizing production efficiency, resource allocation, and production flexibility. This study reviews research from 2014 to 2024 on shop floor scheduling addressing dual-resource constraints, worker assignment, and human–machine collaboration, analyzing their contributions across problem modeling, optimization objectives, and human factor integration. Our analysis reveals an insufficient incorporation of human-centric considerations within the current scheduling framework from the Industry 5.0 perspective. To address this gap, we propose the concept of human-centric shop floor scheduling (HCSFS) and identify four characteristics: efficiency-human (E-H) first; dynamics and uncertainty; data-intensive systems; and interdisciplinary synergy. We further highlight three major challenges for HCSFS: managing multi-objective trade-offs, redefining scheduling problem models, and embedding techno-ethical integration. Finally, future directions are discussed to advance HCSFS in the context of Industry 5.0.</div></div>","PeriodicalId":16227,"journal":{"name":"Journal of Manufacturing Systems","volume":"82 ","pages":"Pages 531-546"},"PeriodicalIF":12.2,"publicationDate":"2025-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144662445","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

Review of recent applications and future perspectives on process monitoring approaches in industrial processes 回顾了工业过程过程监测方法的最新应用和未来前景

IF 12.2 1区工程技术

Journal of Manufacturing Systems Pub Date : 2025-07-14 DOI: 10.1016/j.jmsy.2025.07.002

Shijin Li, Binghai Zhou, Jilin Shang, Xufei Chen, Jianbo Yu

{"title":"Review of recent applications and future perspectives on process monitoring approaches in industrial processes","authors":"Shijin Li, Binghai Zhou, Jilin Shang, Xufei Chen, Jianbo Yu","doi":"10.1016/j.jmsy.2025.07.002","DOIUrl":"10.1016/j.jmsy.2025.07.002","url":null,"abstract":"<div><div>Process monitoring is essential in industrial production, as it ensures product quality and production efficiency through real-time data monitoring and analysis during the manufacturing process. Process monitoring generally includes four procedures: fault detection, fault diagnosis, fault isolation and root cause diagnosis. However, few current works present comprehensive review papers covering the four aspects. Thus, this review presents a timely and comprehensive retrospective analysis of process monitoring techniques and provides an in-depth review of research developments in process monitoring across different scopes. Firstly, this review discusses the characteristics and applications of both traditional machine learning-based and deep learning-based process monitoring methods, which offer a comprehensive comparison and evaluation of their respective strengths and limitations. Secondly, the extensions, prospects and challenges in data-driven process monitoring (i.e., adaptive, interpretable approaches as well as contrastive learning and meta-learning-based techniques) are discussed to lay a solid foundation for future research. Thirdly, the application procedures, including fault detection, fault diagnosis, fault isolation and root cause diagnosis, are elaborated to provide valuable research references and insights for both academics and practitioners. Finally, the existing challenges and promising research directions are discussed, which can pave the way for future research and contribute to the advancement in process monitoring.</div></div>","PeriodicalId":16227,"journal":{"name":"Journal of Manufacturing Systems","volume":"82 ","pages":"Pages 509-530"},"PeriodicalIF":12.2,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144623782","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