{"title":"A framework to define, design and construct digital twins in the mining industry","authors":"Luke van Eyk, P. Stephan Heyns","doi":"10.1016/j.cie.2024.110805","DOIUrl":null,"url":null,"abstract":"<div><div>The mining industry is set to increasingly use technological innovations surrounding digitalisation, particularly in the context of the fourth industrial revolution, to address current productivity challenges and safety concerns. Digital twins serve as an enabling technology for many digitalisation-based technological innovations. However, there is currently a lack of a comprehensive understanding of the digital twin concept within the mining industry. This paper presents a framework customised to mining which delineates various dimensions, model types and properties associated with a digital twin. The framework establishes a shared understanding of the concept, serving as a blueprint for the development of future digital twin works in the mining industry. The framework is enriched by accompanying model selection tools which could aid new users in developing digital twins within the proposed framework. Two case studies depicting existing mining digital twins are presented and deconstructed within the proposed framework. These case studies illustrate the framework’s ability to effectively identify various digital twin types, instilling confidence in the framework’s ability to thoroughly deconstruct existing works whilst simultaneously serving as an effective tool to construct future digital twins.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"200 ","pages":"Article 110805"},"PeriodicalIF":6.7000,"publicationDate":"2025-02-01","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/S0360835224009276","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 mining industry is set to increasingly use technological innovations surrounding digitalisation, particularly in the context of the fourth industrial revolution, to address current productivity challenges and safety concerns. Digital twins serve as an enabling technology for many digitalisation-based technological innovations. However, there is currently a lack of a comprehensive understanding of the digital twin concept within the mining industry. This paper presents a framework customised to mining which delineates various dimensions, model types and properties associated with a digital twin. The framework establishes a shared understanding of the concept, serving as a blueprint for the development of future digital twin works in the mining industry. The framework is enriched by accompanying model selection tools which could aid new users in developing digital twins within the proposed framework. Two case studies depicting existing mining digital twins are presented and deconstructed within the proposed framework. These case studies illustrate the framework’s ability to effectively identify various digital twin types, instilling confidence in the framework’s ability to thoroughly deconstruct existing works whilst simultaneously serving as an effective tool to construct future digital twins.
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.