Journal article
A literature review on the artificial intelligence in manufacturing systems under industry 5.0
International journal of production research, pp 1-42
03 Mar 2026
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Industry 5.0 is characterised by a human-centric, sustainable, and resilient manufacturing paradigm, placing new demands on industrial systems. Within this evolving context, Artificial Intelligence has emerged as a key driver, making a systematic understanding of its applications and challenges essential. While Industry 4.0 has been widely studied, comprehensive reviews of AI's role in Industry 5.0 remain limited. To address this gap, this paper conducts a systematic literature review using a three-stage search strategy across major databases. The review outlines the envisioned characteristics of Industry 5.0 systems and analyzes AI applications: enabling human-centric manufacturing through intelligent interaction and scheduling, enhancing resilience via fault diagnosis and predictive maintenance, and supporting sustainability through circular practices and energy conservation. It further identifies three key challenges: (i) technical issues such as data scarcity and cybersecurity risks; (ii) barriers in human-machine collaboration; and (iii) ethical and privacy concerns in data governance. Overall, AI is crucial not only for efficiency but also as a strategic enabler of human-centricity, resilience, and sustainability. However, current applications remain efficiency-driven, with limited integration of broader objectives. Future work should emphasise system optimisation, explainable AI, generative AI for secure, transparent, and sustainable manufacturing for Industry 5.0.
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Details
- Title
- A literature review on the artificial intelligence in manufacturing systems under industry 5.0
- Creators
- Yuchen Pan - Renmin University of ChinaZilin Huang - Renmin University of ChinaBenjamin Lev - Drexel University, Decision Sciences (and Management Information Systems)Lu Xu - Renmin University of ChinaDavid Olson - Univ Nebraska Lincoln, Coll Business Adm, Lincoln, NE USA
- Publication Details
- International journal of production research, pp 1-42
- Publisher
- Taylor & Francis
- Number of pages
- 42
- Grant note
- National Natural Science Foundation of China; National Natural Science Foundation of China (NSFC) 20240484564, 20250484963 / Beijing Nova Program; Beijing Municipal Science & Technology Commission
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Decision Sciences (and Management Information Systems)
- Web of Science ID
- WOS:001706286300001
- Scopus ID
- 2-s2.0-105032104699
- Other Identifier
- 991022170456204721
UN Sustainable Development Goals (SDGs)
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Source: SDGs in the Output
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Engineering, Industrial
- Engineering, Manufacturing
- Operations Research & Management Science