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An optimization method for shopfloor material handling based on real-time and multi-source manufacturing data

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  • Zhang, Yingfeng
  • Zhang, Geng
  • Du, Wei
  • Wang, Junqiang
  • Ali, Ebad
  • Sun, Shudong

Abstract

With the wide use of auto-ID devices in manufacturing shop floors, it creates a huge number of real-time and multi-source manufacturing data. To make a better decision based on the real-time and multi-source manufacturing data, in this paper, a dynamical optimization model for shopfloor material handling (DOM-SMH) is designed. Contrast to a traditional material handling method, each trolley is an active entity which will request the transport tasks. Then, the optimal transport tasks will be assigned to the optimal trolleys according to their real-time status. The key technologies such as intelligent trolley, real-time information exchange and optimization for material handling tasks are designed and developed to implement the dynamical optimization model. The presented method is demonstrated by a case study, and its effectiveness is also analyzed and discussed through the empty-loading ratio and total distance.

Suggested Citation

  • Zhang, Yingfeng & Zhang, Geng & Du, Wei & Wang, Junqiang & Ali, Ebad & Sun, Shudong, 2015. "An optimization method for shopfloor material handling based on real-time and multi-source manufacturing data," International Journal of Production Economics, Elsevier, vol. 165(C), pages 282-292.
    • Handle: RePEc:eee:proeco:v:165:y:2015:i:c:p:282-292
    DOI: 10.1016/j.ijpe.2014.12.029
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    Cited by:

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    2. Tan, Weng Chun & Sidhu, Manjit Singh, 2022. "Review of RFID and IoT integration in supply chain management," Operations Research Perspectives, Elsevier, vol. 9(C).
    3. Ting Qu & Matthias Thürer & Junhao Wang & Zongzhong Wang & Huan Fu & Congdong Li & George Q. Huang, 2017. "System dynamics analysis for an Internet-of-Things-enabled production logistics system," International Journal of Production Research, Taylor & Francis Journals, vol. 55(9), pages 2622-2649, May.
    4. Yingfeng Zhang & Sichao Liu & Yang Liu & Rui Li, 2016. "Smart box-enabled product–service system for cloud logistics," International Journal of Production Research, Taylor & Francis Journals, vol. 54(22), pages 6693-6706, November.
    5. Morett, Emilio & Tappia, Elena & Melacini, Marco, 2021. "Scheduling mobile robots in part feeding systems," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Ringle, Christian M. & Blecker, Thorsten (ed.), Adapting to the Future: How Digitalization Shapes Sustainable Logistics and Resilient Supply Chain Management. Proceedings of the Hamburg Internationa, volume 31, pages 129-149, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    6. Yingfeng Zhang & Geng Zhang & Yang Liu & Di Hu, 2017. "Research on services encapsulation and virtualization access model of machine for cloud manufacturing," Journal of Intelligent Manufacturing, Springer, vol. 28(5), pages 1109-1123, June.

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