Call for Papers: Article Collection on Recent Advances of AI for Engineering Service and Maintenance

Since the arrival of Industry 4.0, manufacturing is in the process of undergoing a significant transformation to become more intelligent. The development of intelligent manufacturing gave birth to a new generation of industrial systems which is expected to be operative under a high level of functionality, reliability, and resilience, to meet the high-quality engineering service and maintenance demands from the systems operators and end-users. Engineering service and maintenance are the cores of operation management, which helps to maximize not only availability, productivity and profitability but even the asset lifetime. Such requirements of engineering service and maintenance call for actions from the research community, to confront the new challenges facing.

Artificial intelligence (AI) has recently become a power-engine transforming various research and applications in the manufacturing sector and providing vibrant solutions to service and maintenance. The recent advances of AI such as computing vision, deep learning, and knowledge graph, have significantly unlocked their potential across a broad spectrum of research offering exciting possibilities. To fully embrace the vision of emerging AI for engineering service and maintenance in the new era, this article collection is intended to solicit and report the latest research progress on the cutting-edge topics relevant to AI for engineering service and maintenance. The topics of the article collection include, but are not limited to:

  • Review of AI for engineering service and maintenance
  • Graph and hypergraph-embedding theories and engineering service and maintenance
  • Smart service and maintenance systems design & development
  • Service and maintenance requirement management and concept evaluationExplainable AI for engineering service and maintenance
  • Deep learning modelling for engineering service and maintenance
  • Knowledge-graph aided engineering service and maintenance
  • Case studies on engineering service and maintenance
  • AI for maintenance, spare part inventory, and availability optimization
  • AI for reliability & resilience of complex systems
  • AI for maintenance & resilience optimization under uncertainties

Guest Editors

Dr. Chong Chen
Guangdong Provincial Key Laboratory of Cyber-Physical System, Guangdong University of Technology, Guangzhou, China

Prof. Dr. Dazhong Wu
Department of Mechanical and Aerospace Engineering, University of Central Florida, USA

Prof. Dr. Ying Liu
Department of Mechanical Engineering, School of Engineering, Cardiff University, UK

Manuscript Submission Information

All manuscripts must be submitted through the manuscripts system at https://www.editorialmanager.com/atis/default.aspx

Please select the designated Special Issue in the additional information Questionnaire. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page.

Submission Deadline

25 April 2022