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).

Abstract
1. 서 론
2. 문헌 연구
    2.1 선행연구
    2.2 다양한 분야에 적용된 연구
3. 연구 방법
    3.1 연구 목적
    3.2 연구 방법
4. 분석 결과
    4.1 공정 프로세스 모델 분석
    4.2 설비 분석
    4.3 통과 수율 분석
5. 결 론
6. References

• 김태성(금오공과대학교 산업공학부) | Taesung Kim (School of Industrial Engineering, Kumoh National Institute of Technology) Corresponding Author