Submit a Manuscript to the Journal

International Journal of Production Research

For a Special Issue on

Crowd intelligence driven resilient production and operations management

Manuscript deadline
01 December 2024

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Special Issue Editor(s)

Kai Ding (Managing Editor), Institute of Smart Manufacturing Systems, Chang'an University, China
[email protected]

Felix T. S. Chan (Lead Editor) , Department of Decision Sciences, School of Business, Macau University of Science and Technology, Macao SAR, China
[email protected]

Lihui Wang, Department of Production Engineering, KTH Royal Institute of Technology, Sweden
[email protected]

Ming K. Lim, Adam Smith Business School, University of Glasgow, United Kingdom
[email protected]

Angappa Gunasekaran, School of Business Administration, Penn State Harrisburg, USA
[email protected]

John P. T. Mo, School of Engineering, RMIT University, Australia
[email protected]

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Crowd intelligence driven resilient production and operations management

AIMS AND SCOPE

Industry 5.0 creates a natural and intelligent human-machine collaboration vision to realize resilient manufacturing ranging from production lines, shop floors, factories, and supply chains. Based on the new IT-driven Industry 4.0 outcomes, The crowd intelligence with the fusion of humans, machines, and things and human-centric artificial intelligence is expected to empower the future manufacturing industry and reform the production and operations management paradigm.

Heterogeneous crowd intelligence has been attracting much attention from both academia and industries. Research efforts have been devoted to the human-machine symbiosis, human-robot collaboration, and human-centric smart manufacturing, which applies industrial AI, digital twin, blockchain, and other technologies to enhance the human-machine or human-robot co-intelligence. Heterogeneous crowd sensing, crowd-agent distributed learning, hybrid-augmented learning, multi-agent gaming, and crowd decision-making are some of the active emerge research areas. However, there are still much work to do on crowd intelligence to facilitate the resilient production and operations management. For example, how to explore the potential of crowd intelligence to reform manufacturing systems; how to realize the hybrid Co-X intelligence to reshape production organization structures and enable the autonomous manufacturing principles; how to ensure the accuracy, resiliency and credibility of human-machine collaboration processes; how to excavate the implications from heterogeneous collaborative manufacturing networks, and so on.

The aim of this special issue is to provide original and latest contributions on crowd intelligence driven resilient 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.

TOPICS COVERED

The following topics are included, but are not limited to:

  • The emergence mechanism and dynamics modeling of crowd intelligence.
  • Crowd intelligence driven manufacturing systems for factory of the future.
  • New principles and mechanisms for crowd intelligence and human-centric artificial intelligence in Industry 5.0.
  • Human-machine-thing gaming and teaming for resilient production and operations management.
  • Hybrid Co-X (perception, decision-making, control, optimization, learning, etc.) intelligence for resilient production and operations management.
  • Industrial knowledge graph for resilient production and operations management.
  • Blockchain-based credibility enhancement of manufacturing operations and supply chain management.
  • Modeling and analysis of heterogeneous collaborative manufacturing network
  • Other related research topics.

REFERENCES

Ivanov D. The Industry 5.0 framework: viability-based integration of the resilience, sustainability, and human-centricity perspectives. International Journal of Production Research, 2023, 61(5): 1683-1695.

Rozanec JM, Novalija I, Zajec P, et al. Human-centric artificial intelligence architecture for industry 5.0 applications. International Journal of Production Research, 2023, 61(20): 6847-6872.

Pelicciari M, Prati E, Pelicciari M. A framework to design smart manufacturing systems for Industry 5.0 based on the human-automation symbiosis. International Journal of Computer Integrated Manufacturing, 2023, doi: 10.1080/0951192X.2023.2257634

Zhang C, Wang ZH, Zhou GH, et al. Towards new-generation human-centric smart manufacturing in Industry 5.0: A systematic review. Advanced Engineering Informatics, 2023, 57: 102121.

Leng J, Zhong Y, Lin Z, et al. Towards Resilience in Industry 5.0: A Decentralized Autonomous Manufacturing Paradigm. Journal of Manufacturing Systems, 2023, 71: 95-114.

Ding K, Chan FTS, Zhang XD, et al. Defining a Digital Twin-based Cyber-Physical Production System for autonomous manufacturing in smart shop floors. International Journal of Production Research, 2019, 57(20):6315-6334.

Wang L, Gao R, V√°ncza J, et al. Symbiotic human-robot collaborative assembly. CIRP Annals-Manufacturing Technology, 2019, 68(2): 701-726.

Guo B, Liu Y, Liu SC, et al. CrowdHMT: Crowd Intelligence with the Deep Fusion of Human, Machine, and IoT. IEEE Internet of Things Journal, 2022, 9(24): 24822-24842.

Submission Instructions

First date for manuscript submission: 1 December 2024

Last date for manuscript submission: 31 May 2025

Notification to authors: 31 July 2025

Revised Manuscript Due: 30 September 2025

Decision Notification: 30 November 2025

Instructions for AuthorsSubmit an Article