Digitalisation and servitisation of machine tools in the era of Industry 4.0: a review

Abstract

Machine tools play a pivotal role in the manufacturing world since their performance significantly affects the product quality and production efficiency. In the era of Industry 4.0, machine tools are expected to have a higher level of accessibility, connectivity, intelligence, adaptivity, and autonomy. With the rapid development and application of various Industry 4.0 technologies, digitalisation and servitisation of machine tools have become a new research trend. However, few review articles on the development of machine tools in the context of Industry 4.0 have been reported. To understand the current status of digitalisation and servitisation of machine tools, this paper provides a systematic literature review combining both bibliometric and qualitative analysis. Our review results provide a comprehensive and in-depth understanding of recent advancements of digitalisation and servitisation of machine tools, including the key enabling technologies, methods, standards, architectures, and applications. Furthermore, we propose a novel conceptual framework of Cyber-Physical Machine Tool (CPMT) as a systematic approach to achieving digitalisation and servitisation of next-generation machine tools. Finally, major research issues, challenges, and future research directions are discussed. This work will help researchers and industrial practitioners spark new ideas for developing the next-generation machine tools in the era of Industry 4.0.

KEYWORDS:

• Machine tools
• Industry 4.0
• smart manufacturing
• digitalisation
• servitisation

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This research work was partially supported by the National Natural Science Foundation of China [No. 52105534], and the Research Committee [Project No.: 1-BBXL] and the State Key Laboratory of Ultra-precision Machining Technology [Project No.: 1-ZVT1] of the Hong Kong Polytechnic University, Hong Kong SAR, China.

Notes on contributors

Chao Liu

Chao Liu is currently a Research Assistant Professor in the Department of Industrial and Systems Engineering at The Hong Kong Polytechnic University. He received his Ph.D. in Mechanical Engineering at the University of Auckland, New Zealand, in 2018. He obtained his Bachelor’s degree (2012) and Master’s degree (2014) in Mechanical Engineering both from Northeastern University, China. Prior to joining PolyU, Dr. Liu worked as a Postdoctoral Research Associate in the School of Engineering at Cardiff University, U.K. He is a member of SME, a member of State Key Laboratory of Ultra-precision Machining Technology at PolyU, and a Topic Editor for Materials journal. His research interests include Industry 4.0, smart manufacturing, machine tools, digital twin, CPS, IoT, big data analytics, AR, machine learning, metal additive manufacturing, etc.

Pai Zheng

Pai Zheng is currently an Assistant Professor in the Department of Industrial and Systems Engineering, at the Hong Kong Polytechnic University. He received his Ph.D. degree in Mechanical Engineering from the University of Auckland in 2017, Master’s Degree in Mechanical Engineering from Beihang University in 2013, and Dual Bachelor’s Degrees in Engineering from Huazhong University of Science and Technology, in 2010. His research interest includes smart product-service systems, engineering informatics, and manufacturing servitisation. He is a member of IEEE, CMES, and ASME, and serves as the Associate Editor of IET Collaborative Intelligent Manufacturing, and Editorial Board Member for the journal of Advanced Engineering Informatics.

Xun Xu

Xun Xu is a Chair Professor of Manufacturing at the Department of Mechanical Engineering, The University of Auckland. He joined the Department after completing a PhD from the University of Manchester (then UMIST), U.K in 1996. He has been working in the field of intelligent manufacturing solutions for some 30 years. Dr. Xu is an internationally recognised expert in smart manufacturing systems, cloud-based manufacturing and IoT enabled manufacturing. He serves as an Editor-in-Chief, Associate Editor and member of Editorial Board of a number of international journals and has published over 350 research papers. Dr. Xu is the Director of Laboratory for Industry 4.0 Smart Manufacturing Systems (LISMS), the only Laboratory for Industry 4.0 in New Zealand. His current research focus is around the Industry 4.0 technologies, e.g. smart factories, digital twins, cloud manufacturing, Augmented Reality (AR) for manufacturing, big industrial data and data analytics. Dr. Xu is the Fellow of American Society for Mechanical Engineers (ASME) and Engineering New Zealand (EngNZ). In 2020, he is named among of the ‘20 most Influential Professors in Smart Manufacturing’ by the Society of Manufacturing Engineers (SME). He was recognised by Web of Science as a Clarivate™ Highly Cited Researcher in 2020.