Fuzzy Risk-Based Maintenance Strategy with Safety Considerations for the Mining Industry

Abstract

Enterprises today are increasingly seeking maintenance management strategies to ensure that their machines run faultlessly. This problem is particularly relevant in the mining sector, due to the demanding working conditions of underground mines and machines and equipment-operating regimes. Therefore, in this article, the authors proposed a new approach to mining machinery maintenance management, based on the concept of risk-based maintenance (RBM) and taking into account safety issues. The proposed method includes five levels of analysis, of which the first level focuses on hazard analysis, while the next three are connected with a risk evaluation. The final level relates to determining the RBM recommendations. The recommendations are defined in relation to the three main improvement areas: maintenance, safety, and resource availability/allocation. The proposed approach is based on the use of fuzzy logic. To present the possibilities of implementing our method, a case study covering the operation of selected mining machinery in a selected Polish underground mine is presented. In the case of mining machinery, fourteen adverse-event scenarios were identified and investigated; general recommendations were also given. The authors have also indicated further directions of research work to optimize system maintenance strategies, based on the concept of risk-based maintenance. Additionally, the discussion about the implementation possibilities of the approach developed herein is provided.

Integrated Maintenance Management to Increase the Availability of Drilling Equipment: Case Study in a Peruvian Mine

“…Mining activities are carried out by mining operators, who are responsible for providing exploration, development, preparation and exploitation services for mineral deposits. One of the main problems faced by the mining sector occurs when the availability of their equipment decreases [15] Availability is a critical factor in mining industries due to the competitive environment and the high production costs they represent [16]. Low availability arises due to failures in equipment parts or components [15].…”

“…One of the main problems faced by the mining sector occurs when the availability of their equipment decreases [15] Availability is a critical factor in mining industries due to the competitive environment and the high production costs they represent [16]. Low availability arises due to failures in equipment parts or components [15]. Failures are due to the condition of the components during operation and the characteristics of the equipment operation process [15].…”

Developing an Alternate Mineral Transportation System by Evaluating Risk of Truck Accidents in the Mining Industry—A Critical Fuzzy DEMATEL Approach

“…Within the mining industry, the relationship between the specific context of various mining activities and human error rate has previously been modeled using a fuzzy mapping approach [24]. Risk-based maintenance systems have also been developed using fuzzy logic [25].…”

Improvement of Failure Mode and Effects Analysis Using Fuzzy and Adaptive Neuro-Fuzzy Inference System

“…The following systematic review [3] of papers on this topic, produced in the period between 1998 and 2018, points to a very quick increase in annual publications on FMEA improvement in the past two decades, after the publication of the review article by the above mentioned authors in 2013. The majority of papers selected the fuzzy logic system in an attempt to eliminate the disadvantages of the traditional FMEA based on "if-then" rules formed in fuzzy inference system (FIS) and improve upon calculated fuzzy RPN and risk prioritization, for example, for milling machines [4,5], environmental waste water treatment plant [6], automotive industry [7,8] and other industries [9][10][11][12][13][14][15]. For determining risk levels and prioritizing mitigation action for the risks, some authors have taken into account additional variables, for example, costs based on economic impact [16][17][18] or impact of assets, people, environment and/or reputation [19,20].…”