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Spatial–temporal out-of-order execution for advanced planning and scheduling in cyber-physical factories

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Abstract

Cyber-Physical System (CPS) is one of the most promising directions of Industry 4.0 smart manufacturing. Abundant manufacturing data and information are available for decision-makers in real-time thanks to the application of various frontier technologies in CPS. However, the inherent complexity and uncertainty of manufacturing optimization still plague scholars and practitioners and impede further progress of smart manufacturing. The production planning and scheduling is such a complex and stochastic problem that has received considerable research attention. Whereas how to leverage the strengths of CPS for breaking the bottleneck of complexity and uncertainty, is still a question that needs further exploration. This paper proposes a novel “divide and conquer” approach, Spatial–Temporal Out-Of-Order execution (ST-OOO), for achieving real-time planning and scheduling in cyber-physical factories. ST-OOO divides the space and time scopes of a factory into finite areas and intervals to reduce complexity and localize uncertainties so that the original complex optimization problem is decomposed into a set of subproblems with different spatial and temporal characteristics. These small-size subproblems can be assembled using data and information visibility and traceability, and then solved in a rolling spatiotemporal manner to generate a global solution. A case study shows that ST-OOO has a well-balanced and more stable performance compared to traditional strategies. Sensitivity analysis is carried out to study the impacts of spatial and temporal scales on the results.

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Funding

The authors would like to acknowledge partial financial supports from funding sources, including HKSAR RGC GRF Project (17203518), the 2019 Guangdong Special Support Talent Program – Innovation and Entrepreneurship Leading Team (China) (2019BT02S593), and 2018 Guangzhou Leading Innovation Team Program (201909010006).

Author information

Authors and Affiliations

  1. Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, 8/F, Haking Wong Building, HKU, Pokfulam Road, Pok Fu Lam, Hong Kong, China

    Mingxing Li, Ray Y. Zhong & George Q. Huang

  2. School of Intelligent Systems Science and Engineering, Institute of Physical Internet, Jinan University (Zhuhai Campus), Zhuhai, 519070, China

    Ting Qu

Authors
  1. Mingxing Li
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  2. Ray Y. Zhong
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  3. Ting Qu
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  4. George Q. Huang
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Contributions

ML: Conceptualization, Methodology, Formal analysis and investigation, Writing - original draft preparation. RYZ: Conceptualization, Writing - review and editing TQ: Conceptualization, Writing - review and editing. GQH: Conceptualization, Methodology, Supervision, Resources, Funding acquisition.

Corresponding author

Correspondence to George Q. Huang.

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Conflict of interest

The authors declare that this manuscript is original, has not been published before and is not currently being considered for publication elsewhere. There are no known conflicts of interest associated with this publication and there has been no significant financial support for this work that could have influenced its outcome. We confirm that the manuscript has been read and approved by all named authors and that there are no other persons who satisfied the criteria for authorship but are not listed. We further confirm that the order of authors listed in the manuscript has been approved by all of us. We understand that the Corresponding Author is the sole contact for the Editorial process (including Editorial Manager and direct communications with the office). He is responsible for communicating with the other authors about progress, submissions of revisions and final approval of proofs. We confirm that we have provided a current, correct email address (gqhuang@hku.hk) which is accessible by the Corresponding Author and which has been configured to accept emails from the editorial office.

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Li, M., Zhong, R.Y., Qu, T. et al. Spatial–temporal out-of-order execution for advanced planning and scheduling in cyber-physical factories. J Intell Manuf 33, 1355–1372 (2022). https://doi.org/10.1007/s10845-020-01727-2

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