Operation twins: production-intralogistics synchronisation in Industry 4.0

Mingxing Li, Daqiang Guo, Ming Li, Ting Qu, George Q. Huang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

12 Citations (Scopus)


The widespread adoption of Industry 4.0 technologies is revolutionising how manufacturing operations are managed and done. This revolution drives manufacturing practitioners to reevaluate their current manufacturing planning and control (MPC) strategies to maintain global competitiveness. The production and intralogistics (PiL) operations within traditional MPC systems are organised separately, which results in inferior overall solutions. PiL operations in a single factory are inherently coupled and interact with each other throughout the entire process, which needs synchronous organisation and operations. This paper introduces a novel concept of operations twins (OT), with vertical twinning and horizontal twining, for achieving PiL synchronisation by leveraging Industry 4.0 technologies and innovative operations management strategies. An Internet-of-Things (IoT)-based vertical twinning method is developed for real-time object-level data collection and information-sharing between PiL. A horizontal twinning mechanism is proposed to support real-time coordination of production and intralogistics operations with real-time information-sharing. A numerical study is carried out, and the results show that OT outperforms the widely used static and dynamic methods regarding the overall stability and typical measures such as makespan, average manufacturing time, and average tardiness under different levels of uncertainties.

Original languageEnglish
Number of pages19
JournalInternational Journal of Production Research
Publication statusAccepted/In press - 2022


  • Industry 4.0
  • manufacturing planning and control
  • operations twins
  • production and intralogistics
  • real-time information-sharing
  • synchronisation

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering


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