Unlocking factors of digital twins for smart manufacturing: a case of emerging economy

IF 3.7 3区 工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS International Journal of Computer Integrated Manufacturing Pub Date : 2023-09-21 DOI:10.1080/0951192x.2023.2257655
Bhaskar B. Gardas, Angappa Gunasekaran, Vaibhav S. Narwane
{"title":"Unlocking factors of digital twins for smart manufacturing: a case of emerging economy","authors":"Bhaskar B. Gardas, Angappa Gunasekaran, Vaibhav S. Narwane","doi":"10.1080/0951192x.2023.2257655","DOIUrl":null,"url":null,"abstract":"ABSTRACTThe Industry 4.0/smart manufacturing paradigm has significantly changed the activities and processes of organizations. Emergent smart manufacturing technology called a ‘Digital Twin’ (DT) aids organizations in enhancing overall performance by creating a virtual prototype of a real system. However, DT technology adoption in emerging economies is in the nascent stage. This research aims to identify the determinants affecting the adoption of DT technology in Indian manufacturing firms. Based on an extensive literature survey and experts’ opinions, 14 determinants were identified, and these determinants were analyzed using a hybrid multi-attribute decision-making approach to understand the contextual relationship and to identify the cause–effect relationship amongst them. Based on these results, the most critical determinants were explored, namely ‘Real-time system operations and tracking’, ‘Integration, the convergence of systems, processes & resources and enterprise collaboration’, ‘Information and Data management within or between the systems’. The manufacturing organizations of emerging economies need to consider these determinants for the effective adoption of DT technology, and policymakers can use the findings of this study to develop appropriate strategies.KEYWORDS: Information managementdigital twinsemerging economiesmanufacturing firmstechnology adoptiondecision-making Disclosure statementNo potential conflict of interest was reported by the author(s).","PeriodicalId":13907,"journal":{"name":"International Journal of Computer Integrated Manufacturing","volume":"31 1","pages":"0"},"PeriodicalIF":3.7000,"publicationDate":"2023-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Computer Integrated Manufacturing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/0951192x.2023.2257655","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 1

Abstract

ABSTRACTThe Industry 4.0/smart manufacturing paradigm has significantly changed the activities and processes of organizations. Emergent smart manufacturing technology called a ‘Digital Twin’ (DT) aids organizations in enhancing overall performance by creating a virtual prototype of a real system. However, DT technology adoption in emerging economies is in the nascent stage. This research aims to identify the determinants affecting the adoption of DT technology in Indian manufacturing firms. Based on an extensive literature survey and experts’ opinions, 14 determinants were identified, and these determinants were analyzed using a hybrid multi-attribute decision-making approach to understand the contextual relationship and to identify the cause–effect relationship amongst them. Based on these results, the most critical determinants were explored, namely ‘Real-time system operations and tracking’, ‘Integration, the convergence of systems, processes & resources and enterprise collaboration’, ‘Information and Data management within or between the systems’. The manufacturing organizations of emerging economies need to consider these determinants for the effective adoption of DT technology, and policymakers can use the findings of this study to develop appropriate strategies.KEYWORDS: Information managementdigital twinsemerging economiesmanufacturing firmstechnology adoptiondecision-making Disclosure statementNo potential conflict of interest was reported by the author(s).
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
为智能制造解锁数字孪生要素:以新兴经济体为例
摘要工业4.0/智能制造范式极大地改变了组织的活动和流程。被称为“数字孪生”(DT)的新兴智能制造技术通过创建真实系统的虚拟原型来帮助组织提高整体绩效。然而,DT技术在新兴经济体的采用尚处于起步阶段。本研究旨在确定影响印度制造企业采用DT技术的决定因素。在广泛的文献调查和专家意见的基础上,确定了14个决定因素,并使用混合多属性决策方法对这些决定因素进行分析,以了解上下文关系并确定它们之间的因果关系。基于这些结果,我们探讨了最关键的决定因素,即“实时系统操作和跟踪”、“系统、流程和资源的集成、融合以及企业协作”、“系统内部或系统之间的信息和数据管理”。新兴经济体的制造业组织需要考虑这些决定因素,以有效采用DT技术,政策制定者可以利用本研究的结果制定适当的策略。关键词:信息管理数字孪生新兴经济体制造企业技术采用决策披露声明作者未报告潜在的利益冲突。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
9.00
自引率
9.80%
发文量
73
审稿时长
10 months
期刊介绍: International Journal of Computer Integrated Manufacturing (IJCIM) reports new research in theory and applications of computer integrated manufacturing. The scope spans mechanical and manufacturing engineering, software and computer engineering as well as automation and control engineering with a particular focus on today’s data driven manufacturing. Terms such as industry 4.0, intelligent manufacturing, digital manufacturing and cyber-physical manufacturing systems are now used to identify the area of knowledge that IJCIM has supported and shaped in its history of more than 30 years. IJCIM continues to grow and has become a key forum for academics and industrial researchers to exchange information and ideas. In response to this interest, IJCIM is now published monthly, enabling the editors to target topical special issues; topics as diverse as digital twins, transdisciplinary engineering, cloud manufacturing, deep learning for manufacturing, service-oriented architectures, dematerialized manufacturing systems, wireless manufacturing and digital enterprise technologies to name a few.
期刊最新文献
Integration of extended reality and CAE in the context of industry 4.0 Real-time tool condition monitoring with the internet of things and machine learning algorithms Flexible automation and intelligent manufacturing highlights: special issue editorial State of the art and future directions of digital twin-enabled smart assembly automation in discrete manufacturing industries Tool wear prediction method based on dual-attention mechanism network
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1