IET Collaborative Intelligent Manufacturing最新文献_第7页

Optimisation of collaborative supply transportation based on traffic road network topology 基于交通路网拓扑的协同供给运输优化

IF 8.2

IET Collaborative Intelligent Manufacturing Pub Date : 2023-04-02 DOI: 10.1049/cim2.12076

Aihui Wang, Xiaobo Han, Wudai Liao, Ping Liu, Jingwen Song, Daming Li

{"title":"Optimisation of collaborative supply transportation based on traffic road network topology","authors":"Aihui Wang, Xiaobo Han, Wudai Liao, Ping Liu, Jingwen Song, Daming Li","doi":"10.1049/cim2.12076","DOIUrl":"10.1049/cim2.12076","url":null,"abstract":"With the rapid development of China's economy, enterprises need to plan their logistics transportation routes reasonably in advance. This will make the transportation service more efficient. For the supplier's transportation service problem, an analysis method of critical path nodes is provided and a multi-supplier collaborative transportation strategy is designed in this article. First, a model for minimising the transportation cost was established, then a path diagram was simulated and the optimal and alternative transportation paths of suppliers based on the k-shortest path algorithm were calculated. In addition, path node availability during COVID-19 is used as a research context in this article. A multi-stage path analysis method was provided by discussing different cases of critical path nodes, which can make a reasonable selection of paths in a timely and effective manner. Finally, simulations of collaborative transportation for suppliers were performed in three scenarios and the results verified the effectiveness of the collaborative transportation strategy. The proposed collaborative transportation strategy of suppliers not only strengthened the synergistic cooperation among suppliers, but also cultivated the potential customer for suppliers in this article. Furthermore, the strategy could improve the flexibility of the supply chain, maximise the overall efficiency and also provide a new solution for the development of logistics and transportation services.","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"5 2","pages":""},"PeriodicalIF":8.2,"publicationDate":"2023-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.12076","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45722056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A review on learning to solve combinatorial optimisation problems in manufacturing 学习解决制造业中的组合优化问题综述

IF 8.2

IET Collaborative Intelligent Manufacturing Pub Date : 2023-03-03 DOI: 10.1049/cim2.12072

Cong Zhang, Yaoxin Wu, Yining Ma, Wen Song, Zhang Le, Zhiguang Cao, Jie Zhang

{"title":"A review on learning to solve combinatorial optimisation problems in manufacturing","authors":"Cong Zhang, Yaoxin Wu, Yining Ma, Wen Song, Zhang Le, Zhiguang Cao, Jie Zhang","doi":"10.1049/cim2.12072","DOIUrl":"10.1049/cim2.12072","url":null,"abstract":"An efficient manufacturing system is key to maintaining a healthy economy today. With the rapid development of science and technology and the progress of human society, the modern manufacturing system is becoming increasingly complex, posing new challenges to both academia and industry. Ever since the beginning of industrialisation, leaps in manufacturing technology have always accompanied technological breakthroughs from other fields, for example, mechanics, physics, and computational science. Recently, machine learning (ML) technology, one of the crucial subjects of artificial intelligence, has made remarkable progress in many areas. This study thoroughly reviews how ML, specifically deep (reinforcement) learning, motivates new ideas for addressing challenging problems in manufacturing systems. We collect the literature targeting three aspects: scheduling, packing, and routing, which correspond to three pivotal cooperative production links of today's manufacturing system, that is, production, packing, and logistics respectively. For each aspect, we first present and discuss the state-of-the-art research. Then we summarise and analyse the development trends and point out future research opportunities and challenges.","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"5 1","pages":""},"PeriodicalIF":8.2,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.12072","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48811465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

Robotic disassembly sequence planning considering parts failure features 考虑零件失效特征的机器人拆卸顺序规划

IF 8.2

IET Collaborative Intelligent Manufacturing Pub Date : 2023-02-24 DOI: 10.1049/cim2.12074

Jia Cui, Can Yang, Jinliang Zhang, Sisi Tian, Jiayi Liu, Wenjun Xu

{"title":"Robotic disassembly sequence planning considering parts failure features","authors":"Jia Cui, Can Yang, Jinliang Zhang, Sisi Tian, Jiayi Liu, Wenjun Xu","doi":"10.1049/cim2.12074","DOIUrl":"10.1049/cim2.12074","url":null,"abstract":"Disassembly is an important step in remanufacturing products. Robotic disassembly helps to improve disassembly efficiency. However, the end-of-life products often have the parts with uncertain quality, which is manifested as wear, fracture, deformation, corrosion, and other failure features. The parts failure features always have impacts on disassembly process. First, the evaluation method of parts failure features is researched, and the quantitative model of parts failure features is constructed using fuzzy models. Then, the disassembly information model is established by considering the influence of different failure degrees on the robotic disassembly process. Afterwards, to generate the optimal disassembly solution, deep reinforcement learning (DRL) is used to solve robotic disassembly sequence planning problem which considers parts failure features. Considering the influence of parts failure features on robotic disassembly time, the states, actions and rewards and environment are designed in DRL. Finally, a case study of the double shaft coupling as a waste product is carried out, and the proposed method is compared with the other methods to verify the effectiveness.","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"5 1","pages":""},"PeriodicalIF":8.2,"publicationDate":"2023-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.12074","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41331718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Block workshop spatial scheduling based on cellular automata modelling and optimization 基于元胞自动机的块车间空间调度建模与优化

IF 8.2

IET Collaborative Intelligent Manufacturing Pub Date : 2023-02-21 DOI: 10.1049/cim2.12075

Yong Chen, Xuanhao Lin, Wenchao Yi

引用次数: 0

A framework and prototype system in support of workflow collaboration and knowledge mining for manufacturing value chains 一种支持制造价值链工作流协作和知识挖掘的框架和原型系统

IF 8.2

IET Collaborative Intelligent Manufacturing Pub Date : 2023-01-09 DOI: 10.1049/cim2.12073

Bo Qin, Peng Peng, Jian Zhang, Hongwei Wang, Ke Ma

{"title":"A framework and prototype system in support of workflow collaboration and knowledge mining for manufacturing value chains","authors":"Bo Qin, Peng Peng, Jian Zhang, Hongwei Wang, Ke Ma","doi":"10.1049/cim2.12073","DOIUrl":"10.1049/cim2.12073","url":null,"abstract":"In the field of industrial design and manufacture, computer-supported collaborative work (CSCW) systems have been widely deployed for better teamwork. However, the traditional CSCW systems have a main drawback in effectively processing and utilising knowledge across different industrial workflows. To bridge this gap, we propose a framework for collaboration between members across the manufacturing value chains to increase efficiency and reduce duplication in team cooperation. The framework contains three parts, namely workflow, knowledge mining, and services. Specifically, the workflow part provides a collaborative environment for multiple users. The knowledge mining part, as the core of the framework, extracts in-context knowledge from workflows. The part of services can interact with users with different users in each workflow, including information recommendation they need in the future or information retrieval they want to know from other workflows. Furthermore, we develop a prototype system for supporting multiple value chains collaboration to verify the effectiveness and efficiency of the framework.","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"5 1","pages":""},"PeriodicalIF":8.2,"publicationDate":"2023-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.12073","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41978510","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","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-parameters dynamic scheduling with energy management for electric vehicle charging stations 基于能量管理的电动汽车充电站多参数动态调度

IF 8.2

IET Collaborative Intelligent Manufacturing Pub Date : 2022-12-08 DOI: 10.1049/cim2.12068

Haodong Wang, Ning Chen, Zan Liu, Songwei Zhang, Zhiguo Li, Tie Qiu

引用次数: 0

Trusted and secure composite digital twin architecture for collaborative ecosystems 用于协作生态系统的可信和安全组合数字孪生体系结构

IF 8.2

IET Collaborative Intelligent Manufacturing Pub Date : 2022-11-24 DOI: 10.1049/cim2.12070

Pasindu Manisha Kuruppuarachchi, Susan Rea, Alan McGibney

{"title":"Trusted and secure composite digital twin architecture for collaborative ecosystems","authors":"Pasindu Manisha Kuruppuarachchi, Susan Rea, Alan McGibney","doi":"10.1049/cim2.12070","DOIUrl":"10.1049/cim2.12070","url":null,"abstract":"Digitalisation creates new opportunities for businesses to implement and manage collaborative ecosystems both internally and externally. Digital twin (DT) is a rapidly emerging technology that can be used to facilitate new models of interaction and sharing of information. DT is the digital version of a physical process or asset that can be used to model, manage, and optimise its physical counterpart. Connecting multiple DTs is vital to provide a holistic integration and view across complex ecosystems. To create a DT-based collaborative ecosystem architecture, the following concerns need to be addressed. Trust is a fundamental requirement because multiple parties will work together as part of a composite DT. Interoperability is essential, as DTs from various domains will be required to interconnect and operate seamlessly. Finally, the governance is challenging as different scenarios require various mechanisms and governance structures. This study presents an architecture to enable multiple DT-based collaborative ecosystems, and example use case scenarios to demonstrate its applicability in collaborative manufacturing.","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"5 1","pages":""},"PeriodicalIF":8.2,"publicationDate":"2022-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.12070","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44640196","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

A hybrid model for value-added process analysis of manufacturing value chains 制造价值链增值过程分析的混合模型

IF 8.2

IET Collaborative Intelligent Manufacturing Pub Date : 2022-11-19 DOI: 10.1049/cim2.12071

Jingwen Song, Aihui Wang, Ping Liu, Daming Li, Xiaobo Han, Yuhao Yan

{"title":"A hybrid model for value-added process analysis of manufacturing value chains","authors":"Jingwen Song, Aihui Wang, Ping Liu, Daming Li, Xiaobo Han, Yuhao Yan","doi":"10.1049/cim2.12071","DOIUrl":"10.1049/cim2.12071","url":null,"abstract":"In the digital era, realising intelligent digital transformation is a major challenge in the manufacturing field. Digital transformation means bringing more profit appreciation. To improve the analysis reliability of value-added processes, this study proposes a method for assessing enterprises value-adding activities. For this purpose, a hybrid model is constructed based on data and mathematics, bridged by a server. The research builds an element group model that identifies data from different sources, and also gives a mathematical model to describe the relationship of the supply, marketing and service. Taking an automobile manufacturing value chain as an example, to theoretically analyse the composition of value-added activities. Then, the assembly process of an automobile manufacturing plant was used as a value-added case study. The simulation results show the impact of changing production layout and product handling angle on the whole value chain. The study can provide new ideas for the intelligent digital transformation of the manufacturing industry.","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"5 1","pages":""},"PeriodicalIF":8.2,"publicationDate":"2022-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.12071","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49349611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A taxonomy of factors influencing worker's performance in human–robot collaboration 人机协作中影响员工绩效的因素分类

IF 8.2

IET Collaborative Intelligent Manufacturing Pub Date : 2022-11-11 DOI: 10.1049/cim2.12069

Valentina Di Pasquale, Valentina De Simone, Valeria Giubileo, Salvatore Miranda

{"title":"A taxonomy of factors influencing worker's performance in human–robot collaboration","authors":"Valentina Di Pasquale, Valentina De Simone, Valeria Giubileo, Salvatore Miranda","doi":"10.1049/cim2.12069","DOIUrl":"10.1049/cim2.12069","url":null,"abstract":"The occurrence of human errors significantly affects the performance and economic results of production systems. In this context, Human Reliability Analysis (HRA) methods play a key role in assessing the reliability of a man–machine system. Several HRA methods use Performance-Shaping Factors (PSFs), that is, all the aspects of human behaviour and environment that can affect human performance, to evaluate the Human Error Probability (HEP). However, despite the greater emphasis given by researchers to define of PSFs in recent years, the changes caused by the new enabling technologies implemented in manufacturing systems and derived from the Industry 4.0 paradigm have not yet been fully explored. Focussing on Human–Robot Collaboration (HRC) in production systems, the authors aim to define a PSF taxonomy that is useful for HEP evaluations in collaborative environments. To the best of the authors' knowledge, HRA approaches have not been investigated yet for HRC applications. The proposed taxonomy, which results from the integration of the most significant factors impacting workers' performance in HRC into the PSFs provided by an HRA method, can represent an important contribution for researchers and practitioners towards improving HRA methods and their applications in the context of Industry 4.0.","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"5 1","pages":""},"PeriodicalIF":8.2,"publicationDate":"2022-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.12069","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46019657","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Shaping the role of the digital twins for human-robot dyad: Connotations, scenarios, and future perspectives 塑造数字双胞胎在人类-机器人二元组合中的作用:内涵、场景和未来前景

IF 8.2

IET Collaborative Intelligent Manufacturing Pub Date : 2022-10-03 DOI: 10.1049/cim2.12066

Mohaiad Elbasheer, Francesco Longo, Giovanni Mirabelli, Letizia Nicoletti, Antonio Padovano, Vittorio Solina

引用次数: 4