Journal of the Korea Safety Management & Science (대한안전경영과학회지)

Korea Safety Management & Science (대한안전경영과학회)
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On a Study of Reliability-Based MTTF Derivation and Parts Requirement Prediction for Securing Safety of Robot-Based Cargo Loading System

화물 상차 로봇 시스템의 안전성 확보를 위한 신뢰성 기반 MTTF 도출 및 부품소요량 예측 연구

  • Myung-Sung Kim (Department of Systems Engineering, AJOU University) ;
  • Young-Min Kim (Department of Systems Engineering, AJOU University)
  • 김명성 (아주대학교 시스템공학과) ;
  • 김영민 (아주대학교 시스템공학과)
  • Received : 2023.02.01
  • Accepted : 2023.03.13
  • Published : 2023.03.31
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Abstract

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.

Keywords

Acknowledgement

본 연구는 국가교통과학기술진흥원의 국가연구개발사업의 연구비 지원으로 수행되었음(21HCLP-C162730-01).

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