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30 November 2021
International Journal of Production Research
Special Issue Editor(s)
Prof. Felix T. S. Chan,
Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong
Dr. Kai Ding,
Institute of Smart Manufacturing Systems, Chang'an University , Xi’an, China
Industrial Intelligence-driven Production and Operations Management
The fourth industrial revolution has been driving the transformation of manufacturing enterprises. The rapid development of new information technologies (ITs), e.g. Industrial Internet of Things (IIoT), big data, cyber-physical systems (CPS), digital twins (DT), Blockchain, and new generation of artificial intelligence (AI), empowers manufacturing enterprises to create an industrial intelligence-driven production environment. This trend in turn stimulates the development of advanced operation technologies (OTs) that are applied in manufacturing enterprises. With the integration of ITs and OTs, industrial intelligence-driven advanced production and operations management methods can be proposed to upgrade the manufacturing enterprises’ production performance in transparency, controllability, efficiency, flexibility, reconfigurability, low carbon emission, and finally intelligence.
This research area has been attracting more and more attention from both academia and industry. There are many research efforts on the application of new ITs in the manufacturing sectors, such as the Industrial Internet of Things platform for collaborative and customized manufacturing, the digital twin shop floor for close-loop production control, big data-enabled manufacturing knowledge mining for autonomous production decision-makings, cyber-physical system-based machine status monitoring for Prognostic and Health Management (PHM), and so on. Considering the manufacturing sectors cover production planning, monitoring, scheduling, optimization, quality assurance, lean production logistics, human-robot collaboration and many others, there is still ample room to do research on industrial intelligence-driven production and operations management so as to realize intelligent manufacturing in enterprises.
The aim of this special issue is to encourage original and latest contributions, and to review and survey research and development on industrial intelligence-driven production and operations management, focusing on state-of-the-art and potential future approaches and technologies and providing a good starting point for researchers entering these research areas. The special issue will explore new approaches and perspectives of industrial intelligence-driven production and operations management. It is intended to collect a series of leading and high-quality papers on ideas, approaches, and technologies applied for industrial intelligence-driven production and operations management, especially the application of digital twins and industrial AI.
Topics include but are not limited to the following areas:
- High-fidelity and high-confidence modeling of digital twin shop floors
- Modeling and analysis of industrial AI-driven production systems
- Knowledge graph modeling and extending for production decision-making
- Data- and knowledge-driven production control in digital twin shop floors
- Blockchain-based autonomous production execution and quality assurance
- Dynamic planning and adaptive scheduling in intelligent production systems
- Industrial AI-driven low-carbon manufacturing performance evaluation
- Big data-driven operations analysis of production and logistics in manufacturing enterprises
- Applications and case studies in intelligent production and operations management
- Other related research topics
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Before the deadline of November 30th, 2021, authors should submit their manuscripts online. All submitted manuscripts will be subject to the journal’s review process. Submitted papers should not have been previously published or be currently under consideration for publication elsewhere.
- Deadline for submission : November 30th 2021 (tentative)
- Notification of acceptance: May 31, 2022 (tentative)
- Publication of Special Issue: August 31, 2022 (tentative)
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