期刊
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
卷 61, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.rcim.2019.101849
关键词
Cyber physical system (CPS); Material handling; Shop-floor; Prediction model; Remaining processing time; Large-size product
资金
- National Science Foundation of China [51675441]
- National Key Research and Development Program of China [2018YFB1703402]
- 111 Project Grant [B13044]
Cyber physical system (CPS) enables companies to keep high traceability and controllability in manufacturing for better quality and improved productivity. However, several challenges including excessively long waiting time and a serious waste of energy still exist on the shop-floor where limited buffer exists for each machine (e.g., shop-floor that manufactures large-size products). The production logistics tasks are released after work-inprocesses (WIPs) are processed, and the machines will be occupied before trolleys arrival when using passive material handling strategy. To address this issue, a proactive material handling method for CPS enabled shop-floor (CPS-PMH) is proposed. Firstly, the manufacturing resources (machines and trolleys) are made smart by applying CPS technologies so that they are able to sense, act, interact and behave within a smart environment. Secondly, a shop-floor digital twin model is created, aiming to reflect their status just like real-life objects, and key production performance indicators can be analysed timely. Then, a time-weighted multiple linear regression method (TWMLR) is proposed to forecast the remaining processing time of WIPs. A proactive material handling model is designed to allocate smart trolleys optimally. Finally, a case study from Southern China is used to validate the proposed method and results show that the proposed CPS-PMH can largely reduce the total non-value-added energy consumption of manufacturing resources and optimize the routes of smart trolleys.
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