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Synchronization in manufacturing systems: quantification and relation to logistics performance

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  • Stanislav Chankov
  • Marc-Thorsten Hütt
  • Julia Bendul

Abstract

The term ‘synchronization’ in manufacturing refers to the provision of the right components to the subsequent production steps at the right moment in time. It is widely assumed that synchronization is beneficial to the logistics performance of manufacturing systems. However, it has been shown that synchronization phenomena can be detrimental to systems in which they emerge. To study if synchronization phenomena also occur in and affect manufacturing systems’ performance, a formal quantification and holistic understanding of the types of synchronization phenomena emerging in manufacturing are needed. This article aims to fill this research gap by developing synchronization measures for manufacturing systems, applying these measures to real-world production feedback data and utilising them to test the assumption about synchronization’s beneficial effect on logistics performance. We identify two distinct synchronization types occurring in manufacturing systems, logistics and physics synchronization, and show that they are negatively correlated. Further, we show that logistics synchronization and due date performance exhibit anti-correlation and thus question the assumption that synchronization leads to higher efficiency in manufacturing systems. This article aids production managers in designing and optimising production systems, and supports further empirical research in production planning and control and production system design.

Suggested Citation

  • Stanislav Chankov & Marc-Thorsten Hütt & Julia Bendul, 2016. "Synchronization in manufacturing systems: quantification and relation to logistics performance," International Journal of Production Research, Taylor & Francis Journals, vol. 54(20), pages 6033-6051, October.
    • Handle: RePEc:taf:tprsxx:v:54:y:2016:i:20:p:6033-6051
    DOI: 10.1080/00207543.2016.1165876
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    Cited by:

    1. Guo, Daqiang & Li, Mingxing & Lyu, Zhongyuan & Kang, Kai & Wu, Wei & Zhong, Ray Y. & Huang, George Q., 2021. "Synchroperation in industry 4.0 manufacturing," International Journal of Production Economics, Elsevier, vol. 238(C).
    2. Emilio Moretti & Elena Tappia & Martina Mauri & Marco Melacini, 2022. "A performance model for mobile robot-based part feeding systems to supermarkets," Flexible Services and Manufacturing Journal, Springer, vol. 34(3), pages 580-613, September.
    3. Kück, Mirko & Freitag, Michael, 2021. "Forecasting of customer demands for production planning by local k-nearest neighbor models," International Journal of Production Economics, Elsevier, vol. 231(C).
    4. Florian Klug, 2022. "Modelling oscillations in the supply chain: the case of a just-in-sequence supply process from the automotive industry," Journal of Business Economics, Springer, vol. 92(1), pages 85-113, January.
    5. Luo, Hao & Yang, Xuan & Kong, Xiang T.R., 2019. "A synchronized production-warehouse management solution for reengineering the online-offline integrated order fulfillment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 211-230.

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