平台聚合制造服务协作基准:方法与实施

IF 9.1 1区 计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
{"title":"平台聚合制造服务协作基准:方法与实施","authors":"","doi":"10.1016/j.rcim.2024.102853","DOIUrl":null,"url":null,"abstract":"<div><p>In light of the global economic downturn and the intricate division of labor in manufacturing, the imperative for advanced manufacturing services and Manufacturing Service Collaboration (MSC) has escalated significantly. As manufacturing services gravitate towards aggregation on manufacturing service platforms, platform-aggregated MSC has emerged as an inevitable and compelling trend, capturing the attention of researchers worldwide. However, despite the existence of numerous frameworks, models, operational mechanisms, and algorithms proposed for the platform-aggregated MSC, drawing comparisons between these studies remains a complex endeavor. To address this predicament, this article proposes and explores a novel benchmarking methodology for platform-aggregated MSC. By employing complex network theory, a comprehensive model of platform-aggregated MSC is constructed and supplemented with corresponding methodologies for data generation and the configuration of optimization algorithms. Moreover, pertinent performance evaluation metrics are scrutinized to assess their applicability in the context of platform-aggregated MSC. The article culminates with the execution of a series of platform operation experiments designed to test the effectiveness and practicality of the proposed benchmarking system, thereby contributing to the ongoing evolution of the MSC domain.</p></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":null,"pages":null},"PeriodicalIF":9.1000,"publicationDate":"2024-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Benchmarking for platform-aggregated manufacturing service collaboration: Methodology and implementation\",\"authors\":\"\",\"doi\":\"10.1016/j.rcim.2024.102853\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>In light of the global economic downturn and the intricate division of labor in manufacturing, the imperative for advanced manufacturing services and Manufacturing Service Collaboration (MSC) has escalated significantly. As manufacturing services gravitate towards aggregation on manufacturing service platforms, platform-aggregated MSC has emerged as an inevitable and compelling trend, capturing the attention of researchers worldwide. However, despite the existence of numerous frameworks, models, operational mechanisms, and algorithms proposed for the platform-aggregated MSC, drawing comparisons between these studies remains a complex endeavor. To address this predicament, this article proposes and explores a novel benchmarking methodology for platform-aggregated MSC. By employing complex network theory, a comprehensive model of platform-aggregated MSC is constructed and supplemented with corresponding methodologies for data generation and the configuration of optimization algorithms. Moreover, pertinent performance evaluation metrics are scrutinized to assess their applicability in the context of platform-aggregated MSC. The article culminates with the execution of a series of platform operation experiments designed to test the effectiveness and practicality of the proposed benchmarking system, thereby contributing to the ongoing evolution of the MSC domain.</p></div>\",\"PeriodicalId\":21452,\"journal\":{\"name\":\"Robotics and Computer-integrated Manufacturing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":9.1000,\"publicationDate\":\"2024-08-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Robotics and Computer-integrated Manufacturing\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0736584524001406\",\"RegionNum\":1,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Robotics and Computer-integrated Manufacturing","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0736584524001406","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0

摘要

鉴于全球经济衰退和制造业的复杂分工,对先进制造服务和制造服务协作(MSC)的需求显著增加。随着制造服务向制造服务平台聚集,平台聚集型 MSC 已成为一种不可避免且引人注目的趋势,吸引了全球研究人员的目光。然而,尽管针对平台聚合式 MSC 提出了许多框架、模型、运行机制和算法,但对这些研究进行比较仍然是一项复杂的工作。为解决这一难题,本文提出并探索了一种新型的平台聚合式 MSC 基准测试方法。通过运用复杂网络理论,构建了平台聚合式 MSC 的综合模型,并辅以相应的数据生成和优化算法配置方法。此外,还仔细研究了相关的性能评估指标,以评估它们在平台聚合式 MSC 中的适用性。文章最后还进行了一系列平台运行实验,旨在测试拟议基准系统的有效性和实用性,从而为 MSC 领域的持续发展做出贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Benchmarking for platform-aggregated manufacturing service collaboration: Methodology and implementation

In light of the global economic downturn and the intricate division of labor in manufacturing, the imperative for advanced manufacturing services and Manufacturing Service Collaboration (MSC) has escalated significantly. As manufacturing services gravitate towards aggregation on manufacturing service platforms, platform-aggregated MSC has emerged as an inevitable and compelling trend, capturing the attention of researchers worldwide. However, despite the existence of numerous frameworks, models, operational mechanisms, and algorithms proposed for the platform-aggregated MSC, drawing comparisons between these studies remains a complex endeavor. To address this predicament, this article proposes and explores a novel benchmarking methodology for platform-aggregated MSC. By employing complex network theory, a comprehensive model of platform-aggregated MSC is constructed and supplemented with corresponding methodologies for data generation and the configuration of optimization algorithms. Moreover, pertinent performance evaluation metrics are scrutinized to assess their applicability in the context of platform-aggregated MSC. The article culminates with the execution of a series of platform operation experiments designed to test the effectiveness and practicality of the proposed benchmarking system, thereby contributing to the ongoing evolution of the MSC domain.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Robotics and Computer-integrated Manufacturing
Robotics and Computer-integrated Manufacturing 工程技术-工程:制造
CiteScore
24.10
自引率
13.50%
发文量
160
审稿时长
50 days
期刊介绍: The journal, Robotics and Computer-Integrated Manufacturing, focuses on sharing research applications that contribute to the development of new or enhanced robotics, manufacturing technologies, and innovative manufacturing strategies that are relevant to industry. Papers that combine theory and experimental validation are preferred, while review papers on current robotics and manufacturing issues are also considered. However, papers on traditional machining processes, modeling and simulation, supply chain management, and resource optimization are generally not within the scope of the journal, as there are more appropriate journals for these topics. Similarly, papers that are overly theoretical or mathematical will be directed to other suitable journals. The journal welcomes original papers in areas such as industrial robotics, human-robot collaboration in manufacturing, cloud-based manufacturing, cyber-physical production systems, big data analytics in manufacturing, smart mechatronics, machine learning, adaptive and sustainable manufacturing, and other fields involving unique manufacturing technologies.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信