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Production and operations management for intelligent manufacturing: a systematic literature review

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  • Liping Zhou
  • Zhibin Jiang
  • Na Geng
  • Yimeng Niu
  • Feng Cui
  • Kefei Liu
  • Nanshan Qi

Abstract

In the context of Industry 4.0, the manufacturing sector is moving from automation towards intelligence. The application of new generation information and communication technologies (ICTs) improves the interconnection and transparency of intelligent manufacturing (IM) systems, which will change how information interacts and work is done, thus changing how work should be managed. These changes require the following characteristics for IM production and operations management (POM): integration, flexibility and networking, autonomous and collaborative decision-making, learning-based operations management, self-optimisation and adaptability, and proactive decision-making. This paper presents the state of the art, current challenges, and future directions of IM-related POM research from the perspectives of these characteristics through a systematic literature review. Descriptive and thematic analyses of 208 research articles published between 2005 and 2020 are provided. The review and discussions focus on five research themes, i.e. value creation mechanisms, resource configuration and capacity planning, production planning, scheduling, and logistics.

Suggested Citation

  • Liping Zhou & Zhibin Jiang & Na Geng & Yimeng Niu & Feng Cui & Kefei Liu & Nanshan Qi, 2022. "Production and operations management for intelligent manufacturing: a systematic literature review," International Journal of Production Research, Taylor & Francis Journals, vol. 60(2), pages 808-846, January.
    • Handle: RePEc:taf:tprsxx:v:60:y:2022:i:2:p:808-846
    DOI: 10.1080/00207543.2021.2017055
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    Cited by:

    1. Zhu, Minghao & Liang, Chen & Yeung, Andy C.L. & Zhou, Honggeng, 2024. "The impact of intelligent manufacturing on labor productivity: An empirical analysis of Chinese listed manufacturing companies," International Journal of Production Economics, Elsevier, vol. 267(C).
    2. Shoujing Zhang & Tiantian Hou & Qing Qu & Adam Glowacz & Samar M. Alqhtani & Muhammad Irfan & Grzegorz Królczyk & Zhixiong Li, 2022. "An Improved Mayfly Method to Solve Distributed Flexible Job Shop Scheduling Problem under Dual Resource Constraints," Sustainability, MDPI, vol. 14(19), pages 1-19, September.
    3. Rubén Jesús Pérez-López & María Mojarro-Magaña & Jesús Everardo Olguín-Tiznado & Claudia Camargo-Wilson & Juan Andrés López-Barreras & Julio Cesar Cano Gutiérrez & Jorge Luis Garcia-Alcaraz, 2022. "Planning, Execution, and Control of Operations in SC Activities—Baja California Manufacturing Case Study," Mathematics, MDPI, vol. 10(19), pages 1-19, September.

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