Usman Tariq, R. Joy, Sung-Heng Wu, M. A. Mahmood, A. Malik, F. Liou
{"title":"A state-of-the-art digital factory integrating digital twin for laser additive and subtractive manufacturing processes","authors":"Usman Tariq, R. Joy, Sung-Heng Wu, M. A. Mahmood, A. Malik, F. Liou","doi":"10.1108/rpj-03-2023-0113","DOIUrl":null,"url":null,"abstract":"\nPurpose\nThis study aims to discuss the state-of-the-art digital factory (DF) development combining digital twins (DTs), sensing devices, laser additive manufacturing (LAM) and subtractive manufacturing (SM) processes. The current shortcomings and outlook of the DF also have been highlighted. A DF is a state-of-the-art manufacturing facility that uses innovative technologies, including automation, artificial intelligence (AI), the Internet of Things, additive manufacturing (AM), SM, hybrid manufacturing (HM), sensors for real-time feedback and control, and a DT, to streamline and improve manufacturing operations.\n\n\nDesign/methodology/approach\nThis study presents a novel perspective on DF development using laser-based AM, SM, sensors and DTs. Recent developments in laser-based AM, SM, sensors and DTs have been compiled. This study has been developed using systematic reviews and meta-analyses (PRISMA) guidelines, discussing literature on the DTs for laser-based AM, particularly laser powder bed fusion and direct energy deposition, in-situ monitoring and control equipment, SM and HM. The principal goal of this study is to highlight the aspects of DF and its development using existing techniques.\n\n\nFindings\nA comprehensive literature review finds a substantial lack of complete techniques that incorporate cyber-physical systems, advanced data analytics, AI, standardized interoperability, human–machine cooperation and scalable adaptability. The suggested DF effectively fills this void by integrating cyber-physical system components, including DT, AM, SM and sensors into the manufacturing process. Using sophisticated data analytics and AI algorithms, the DF facilitates real-time data analysis, predictive maintenance, quality control and optimal resource allocation. In addition, the suggested DF ensures interoperability between diverse devices and systems by emphasizing standardized communication protocols and interfaces. The modular and adaptable architecture of the DF enables scalability and adaptation, allowing for rapid reaction to market conditions.\n\n\nOriginality/value\nBased on the need of DF, this review presents a comprehensive approach to DF development using DTs, sensing devices, LAM and SM processes and provides current progress in this domain.\n","PeriodicalId":20981,"journal":{"name":"Rapid Prototyping Journal","volume":null,"pages":null},"PeriodicalIF":3.4000,"publicationDate":"2023-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Rapid Prototyping Journal","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1108/rpj-03-2023-0113","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}
引用次数: 3
Abstract
Purpose
This study aims to discuss the state-of-the-art digital factory (DF) development combining digital twins (DTs), sensing devices, laser additive manufacturing (LAM) and subtractive manufacturing (SM) processes. The current shortcomings and outlook of the DF also have been highlighted. A DF is a state-of-the-art manufacturing facility that uses innovative technologies, including automation, artificial intelligence (AI), the Internet of Things, additive manufacturing (AM), SM, hybrid manufacturing (HM), sensors for real-time feedback and control, and a DT, to streamline and improve manufacturing operations.
Design/methodology/approach
This study presents a novel perspective on DF development using laser-based AM, SM, sensors and DTs. Recent developments in laser-based AM, SM, sensors and DTs have been compiled. This study has been developed using systematic reviews and meta-analyses (PRISMA) guidelines, discussing literature on the DTs for laser-based AM, particularly laser powder bed fusion and direct energy deposition, in-situ monitoring and control equipment, SM and HM. The principal goal of this study is to highlight the aspects of DF and its development using existing techniques.
Findings
A comprehensive literature review finds a substantial lack of complete techniques that incorporate cyber-physical systems, advanced data analytics, AI, standardized interoperability, human–machine cooperation and scalable adaptability. The suggested DF effectively fills this void by integrating cyber-physical system components, including DT, AM, SM and sensors into the manufacturing process. Using sophisticated data analytics and AI algorithms, the DF facilitates real-time data analysis, predictive maintenance, quality control and optimal resource allocation. In addition, the suggested DF ensures interoperability between diverse devices and systems by emphasizing standardized communication protocols and interfaces. The modular and adaptable architecture of the DF enables scalability and adaptation, allowing for rapid reaction to market conditions.
Originality/value
Based on the need of DF, this review presents a comprehensive approach to DF development using DTs, sensing devices, LAM and SM processes and provides current progress in this domain.
期刊介绍:
Rapid Prototyping Journal concentrates on development in a manufacturing environment but covers applications in other areas, such as medicine and construction. All papers published in this field are scattered over a wide range of international publications, none of which actually specializes in this particular discipline, this journal is a vital resource for anyone involved in additive manufacturing. It draws together important refereed papers on all aspects of AM from distinguished sources all over the world, to give a truly international perspective on this dynamic and exciting area.
-Benchmarking – certification and qualification in AM-
Mass customisation in AM-
Design for AM-
Materials aspects-
Reviews of processes/applications-
CAD and other software aspects-
Enhancement of existing processes-
Integration with design process-
Management implications-
New AM processes-
Novel applications of AM parts-
AM for tooling-
Medical applications-
Reverse engineering in relation to AM-
Additive & Subtractive hybrid manufacturing-
Industrialisation