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A state-of-the-art digital factory integrating digital twin for laser additive and subtractive manufacturing processes

Usman Tariq (Department of Mechanical and Aerospace Engineering, Missouri University of Science and Technology, Rolla, Missouri, USA)
Ranjit Joy (Department of Mechanical and Aerospace Engineering, Missouri University of Science and Technology, Rolla, Missouri, USA)
Sung-Heng Wu (Department of Mechanical and Aerospace Engineering, Missouri University of Science and Technology, Rolla, Missouri, USA)
Muhammad Arif Mahmood (Intelligent Systems Center, Missouri University of Science and Technology, Rolla, Missouri, USA)
Asad Waqar Malik (Intelligent Systems Center, Missouri University of Science and Technology, Rolla, Missouri, USA)
Frank Liou (Department of Mechanical and Aerospace Engineering, Missouri University of Science and Technology, Rolla, Missouri, USA)

Rapid Prototyping Journal

ISSN: 1355-2546

Article publication date: 14 August 2023

Issue publication date: 27 November 2023

573

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.

Keywords

Acknowledgements

This study was partially supported by NSF Grants CMMI 1625736, NSF EEC 1937128, and Intelligent Systems Center (ISC) at Missouri S&T. Their financial support is greatly appreciated.

The author “Asad Waqar Malik” is also affiliated with Department of Computing, National University of Sciences and Technology (NUST), Islamabad 44000, Pakistan.

Citation

Tariq, U., Joy, R., Wu, S.-H., Mahmood, M.A., Malik, A.W. and Liou, F. (2023), "A state-of-the-art digital factory integrating digital twin for laser additive and subtractive manufacturing processes", Rapid Prototyping Journal, Vol. 29 No. 10, pp. 2061-2097. https://doi.org/10.1108/RPJ-03-2023-0113

Publisher

:

Emerald Publishing Limited

Copyright © 2023, Emerald Publishing Limited

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