The purpose of this study is to present a novel indicator for analyzing machine failure based on its idle time and productivity. Existing machine repair plan was limited to machine experts from its manufacturing industries. This study evaluates the repair status of machines and extracts machines that need improvement. In this study, F-RPN was calculated using the etching process data provided by the 2018 PHM Data Challenge. Each S(S: Severity), O(O: Occurence), D(D: Detection) is divided into the idle time of the machine, the number of fault data, and the failure rate, respectively. The repair status of machine is quantified through the F-RPN calculated by multiplying S, O, and D. This study conducts a case study of machine in a semiconductor etching process. The process capability index has the disadvantage of not being able to divide the values outside the range. The performance of this index declines when the manufacturing process is under control, hereby introducing F-RPN to evaluate machine status that are difficult to distinguish by process capability index.

Abstract
1. 서 론
2. 이론적 배경
    2.1 식각(Etching)
    2.2 공정능력지수
    2.3 RPN(Risk Priority Number)
3. 방법론
    3.1 생산 장비 데이터 분석
    3.2 생산 장비의 공정능력지수
    3.3 생산 장비의 F-RPN
    3.4 장비 안정 상태에 따른 관리 순위 도출
4. 실험 및 결과 해석
    4.1 생산 장비 데이터 분석
    4.2 생산 장비의 공정능력지수
    4.3 생산 장비의 F-RPN
    4.4 장비 안정 상태에 따른 관리 순위 도출
5. 결 론
6. References

• 이형근(인하대학교 산업경영공학과) | Hyung-Geun Lee (Department of Industrial Engineering, INHA University)
• 홍용민(인하대학교 산업경영공학과) | Yong-Min Hong (Department of Industrial Engineering, INHA University)
• 강성우(인하대학교 산업경영공학과) | Sung-Woo Kang (Department of Industrial Engineering, INHA University) Corresponding Author