In modern society, the delivery service market has grown explosively due to rapid changes in social structure and the recent COVID-19 pandemic. Therefore, various problems such as injury to workers and an increase in human accidents are occurring due to the loading and unloading of parcels. In order to solve this problem, domestic company n is developing a “robot-based cargo loading and unloading system”. In developing a new technology system, quantitative reliability targets should be set for efficient operation and development. In this paper, reliability analysis was conducted through field data for the pneumatic gripper of the “robot-based cargo loading system”. The reliability of the failure data was analyzed to estimate the distribution parameters and MTTF. Random data was derived for the probability of occurrence of a failure with the estimated value. By repeating the simulation to predict the number and year of failures according to the estimated parameters of the probability distribution, it was proposed as a method that reflects realistic probabilities rather than calculating with simple arithmetic using the average MTTF previously used in the field.

Abstract
1. 서 론
    1.1 연구배경
    1.2 문제 정의
    1.3 관련 선행연구
    1.4 연구수행절차
2. 로봇 기반 화물 상차 시스템 개요 및신뢰성 분석 프로세스 구축
    2.1 상차시스템 구성
    2.2 로봇 기반 화물 상차 시스템 현장 데이터정제 및 추출
    2.3. MTTF와 부품소요량의 관계 및 도출방안
3. MTTF 및 부품소요량 도출 절차 및산출물
    3.1 미니탭 신뢰성 분석을 통한 MTTF 도출
    3.2 평균치를 구하여 신뢰성기반 부품소요량산출
    3.3 LSTM 모델기반의 MTTF 데이터 검증
4. 결론
5. References

• 김명성(아주대학교 시스템공학과) | Myung-Sung Kim (Department of Systems Engineering, AJOU University)
• 김영민(아주대학교 시스템공학과) | Young-Min Kim (Department of Systems Engineering, AJOU University) Corresponding Author