Faculty of Mining, Petroleum & Geophysics, Shahrood University of Technology, Shahrood, Semnan, Iran.
Faculty of Technical & Engineering, Imam Khomeini International University, Qazvin, Iran.
PLoS One. 2021 Mar 19;16(3):e0247650. doi: 10.1371/journal.pone.0247650. eCollection 2021.
Spare-part management has a significant effect on the productivity of mining equipment. The required number of spare parts can be estimated using failure and repair data collected under the name of reliability data. In the mining industry, failure and repair times are decided by the operational environment, rock properties, and the technical and functional behavior of the system. These conditions are heterogeneous and may change significantly from time to time. Such heterogeneity can change equipment's reliability performance and, consequently, the required number of spare parts. Hence, it is necessary for effective spare-part planning to check the heterogeneity among the reliability data. After that, if needed, such heterogeneity should be modeled using an adequate statistical model. Heterogeneity can be categorized into observed and unobserved caused by risk factors. Most spare-part estimation studies ignore the effect of heterogeneity, which can lead to unrealistic estimations. In this study, we introduce the application of a frailty model for modeling the effect of observed and unobserved risk factors on the required number of spare parts for mining equipment. Studies indicate that ignoring the effect of unobservable risk factors can cause a significant bias in estimation.
备件管理对采矿设备的生产力有重大影响。可以使用可靠性数据收集的故障和维修数据来估算所需的备件数量。在采矿业中，故障和维修时间由作业环境、岩石特性以及系统的技术和功能行为决定。这些条件具有异质性，并且可能随时间发生显著变化。这种异质性会改变设备的可靠性性能，从而影响所需备件的数量。因此，为了进行有效的备件规划，有必要检查可靠性数据中的异质性。之后，如果需要，可以使用适当的统计模型对这种异质性进行建模。异质性可以分为由风险因素引起的观察到的和未观察到的。大多数备件估算研究忽略了异质性的影响，这可能导致不切实际的估算。在这项研究中，我们介绍了使用脆弱性模型来模拟观察到的和未观察到的风险因素对采矿设备所需备件数量的影响。研究表明，忽略不可观测风险因素的影响可能会导致估计值出现显著偏差。
