Zaker Hossein Ali Reza, Sayadi Ahmad Reza, Javad Rahimdel Mohammad, Reza Moradi Mohammad
Department of Mining Engineering, Faculty of Engineering, Tarbiat Modares University, Iran.
Department of Mining Engineering, Faculty of Engineering, University of Birjand, Birjand, Iran.
Heliyon. 2024 Jul 18;10(15):e34765. doi: 10.1016/j.heliyon.2024.e34765. eCollection 2024 Aug 15.
Failures in mining machinery can abruptly halt mineral production and operations, emphasizing the indispensable role of humans in maintenance and repair operations. Addressing human errors is crucial for ensuring a safe and reliable system, particularly during maintenance activities where accidents frequently occur. This paper focuses on evaluating Human Reliability (HR) to enhance activity implementation effectiveness. Given the challenge of limited and uncertain data on human errors, this study aims to estimate the probability of human errors using Bayesian networks (BN) under uncertain parameters. Applying this approach to assess HR in the maintenance and repair operations of mining trucks at Golgohar Iron Ore Mine in Iran, the study identifies critical factors influencing error occurrence in a fuzzy environment. The results highlight key factors impacting human error and offer insights into estimating HR with minimal human intervention.
采矿机械故障可能会突然停止矿产生产和运营，这凸显了人员在维护和修理作业中不可或缺的作用。解决人为失误对于确保系统安全可靠至关重要，尤其是在事故频发的维护活动期间。本文着重评估人的可靠性（HR）以提高活动实施效果。鉴于人为失误数据有限且不确定的挑战，本研究旨在在参数不确定的情况下使用贝叶斯网络（BN）估计人为失误的概率。将此方法应用于评估伊朗戈尔戈哈尔铁矿采矿卡车维护和修理作业中的人的可靠性，该研究确定了在模糊环境中影响失误发生的关键因素。结果突出了影响人为失误的关键因素，并为以最少人为干预估计人的可靠性提供了见解。
