Towards sustainable cognitive digital twins: A portfolio management tool for waste mitigation

IF 6.7 1区 工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Computers & Industrial Engineering Pub Date : 2024-11-10 DOI:10.1016/j.cie.2024.110715
Antonio Padovano , Chiara Sammarco , Nasia Balakera , Fotios Konstantinidis
{"title":"Towards sustainable cognitive digital twins: A portfolio management tool for waste mitigation","authors":"Antonio Padovano ,&nbsp;Chiara Sammarco ,&nbsp;Nasia Balakera ,&nbsp;Fotios Konstantinidis","doi":"10.1016/j.cie.2024.110715","DOIUrl":null,"url":null,"abstract":"<div><div>The rapid integration of Cognitive Digital Twins (CDTs) across various industries has revolutionized operational practices, leading to enhanced efficiency and improved decision-making capabilities. However, this technological advancement is accompanied by significant environmental implications, particularly regarding the management of electronic waste (e-waste) and digital waste. While e-waste primarily concerns the disposal of obsolete hardware, digital waste encompasses inefficiencies, redundancies, and unnecessary consumption of computational resources in the digital environment. This paper emphasizes the importance of understanding the lifecycle impacts of CDTs and advocates for the implementation of sustainable practices in their management. To address these challenges, we introduce Digital Twin Portfolio Management (DTPM) as a systematic framework for optimizing the CDT ecosystem. We also present the Digital Twin Triple Bottom Line as a framework for assessing the technical, economic, and environmental impacts of CDT implementations, ensuring that organizations can identify inefficiencies and align their operations with broader sustainability objectives. The findings elucidate the various types of waste generated by CDTs, establishing a critical link between digital asset management and environmental sustainability. Additionally, the study advocates for improved APM practices tailored to the unique challenges posed by CDTs, contributing valuable insights to the evolving discourse on IT portfolio management. Future research directions are also discussed, including the need for expanded case studies and longitudinal investigations to enhance the generalizability and understanding of CDT lifecycle management.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"198 ","pages":"Article 110715"},"PeriodicalIF":6.7000,"publicationDate":"2024-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers & Industrial Engineering","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0360835224008374","RegionNum":1,"RegionCategory":"工程技术","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

Abstract

The rapid integration of Cognitive Digital Twins (CDTs) across various industries has revolutionized operational practices, leading to enhanced efficiency and improved decision-making capabilities. However, this technological advancement is accompanied by significant environmental implications, particularly regarding the management of electronic waste (e-waste) and digital waste. While e-waste primarily concerns the disposal of obsolete hardware, digital waste encompasses inefficiencies, redundancies, and unnecessary consumption of computational resources in the digital environment. This paper emphasizes the importance of understanding the lifecycle impacts of CDTs and advocates for the implementation of sustainable practices in their management. To address these challenges, we introduce Digital Twin Portfolio Management (DTPM) as a systematic framework for optimizing the CDT ecosystem. We also present the Digital Twin Triple Bottom Line as a framework for assessing the technical, economic, and environmental impacts of CDT implementations, ensuring that organizations can identify inefficiencies and align their operations with broader sustainability objectives. The findings elucidate the various types of waste generated by CDTs, establishing a critical link between digital asset management and environmental sustainability. Additionally, the study advocates for improved APM practices tailored to the unique challenges posed by CDTs, contributing valuable insights to the evolving discourse on IT portfolio management. Future research directions are also discussed, including the need for expanded case studies and longitudinal investigations to enhance the generalizability and understanding of CDT lifecycle management.
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
实现可持续的认知数字双胞胎:减少浪费的组合管理工具
认知数字双胞胎(CDTs)在各行各业的快速融合彻底改变了运营实践,提高了效率和决策能力。然而,这一技术进步也带来了重大的环境影响,尤其是在电子废物(e-waste)和数字废物的管理方面。电子垃圾主要涉及过时硬件的处置,而数字垃圾则包括数字环境中的低效、冗余和不必要的计算资源消耗。本文强调了了解 CDT 生命周期影响的重要性,并倡导在 CDT 管理中实施可持续实践。为了应对这些挑战,我们引入了数字孪生组合管理(DTPM)作为优化 CDT 生态系统的系统框架。我们还提出了 "数字孪生三重底线"(Digital Twin Triple Bottom Line),作为评估 CDT 实施的技术、经济和环境影响的框架,确保组织能够识别效率低下的问题,并使其运营符合更广泛的可持续发展目标。研究结果阐明了 CDT 产生的各类废物,在数字资产管理和环境可持续性之间建立了重要联系。此外,该研究还提倡针对 CDT 带来的独特挑战改进 APM 实践,为不断发展的 IT 组合管理讨论提供有价值的见解。研究还讨论了未来的研究方向,包括扩大案例研究和纵向调查的必要性,以增强对 CDT 生命周期管理的普遍性和理解。
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
Computers & Industrial Engineering
Computers & Industrial Engineering 工程技术-工程:工业
CiteScore
12.70
自引率
12.70%
发文量
794
审稿时长
10.6 months
期刊介绍: Computers & Industrial Engineering (CAIE) is dedicated to researchers, educators, and practitioners in industrial engineering and related fields. Pioneering the integration of computers in research, education, and practice, industrial engineering has evolved to make computers and electronic communication integral to its domain. CAIE publishes original contributions focusing on the development of novel computerized methodologies to address industrial engineering problems. It also highlights the applications of these methodologies to issues within the broader industrial engineering and associated communities. The journal actively encourages submissions that push the boundaries of fundamental theories and concepts in industrial engineering techniques.
期刊最新文献
Robotic disassembly of electric vehicle batteries: Technologies and opportunities A location-sizing and routing model for a biomethane production chain fed by municipal waste A reinforcement learning-driven cooperative scatter search for the knapsack problem with forfeits Ergonomic design of Human-Robot collaborative workstation in the Era of Industry 5.0 Towards sustainable cognitive digital twins: A portfolio management tool for waste mitigation
×
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