Journal of the Korea Safety Management & Science (대한안전경영과학회지)

Korea Safety Management & Science (대한안전경영과학회)
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An Empirical Study on Manufacturing Process Mining of Smart Factory

스마트 팩토리의 제조 프로세스 마이닝에 관한 실증 연구

  • Taesung, Kim (School of Industrial Engineering, Kumoh National Institute of Technology)
  • 김태성 (금오공과대학교 산업공학부 )
  • Received : 2022.10.04
  • Accepted : 2022.12.29
  • Published : 2022.12.31
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Abstract

Manufacturing process mining performs various data analyzes of performance on event logs that record production. That is, it analyzes the event log data accumulated in the information system and extracts useful information necessary for business execution. Process data analysis by process mining analyzes actual data extracted from manufacturing execution systems (MES) to enable accurate manufacturing process analysis. In order to continuously manage and improve manufacturing and manufacturing processes, there is a need to structure, monitor and analyze the processes, but there is a lack of suitable technology to use. The purpose of this research is to propose a manufacturing process analysis method using process mining and to establish a manufacturing process mining system by analyzing empirical data. In this research, the manufacturing process was analyzed by process mining technology using transaction data extracted from MES. A relationship model of the manufacturing process and equipment was derived, and various performance analyzes were performed on the derived process model from the viewpoint of work, equipment, and time. The results of this analysis are highly effective in shortening process lead times (bottleneck analysis, time analysis), improving productivity (throughput analysis), and reducing costs (equipment analysis).

Keywords

Acknowledgement

This paper was supported by general research fund, Kumoh National Institute of Technology.

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