Affiliation:
1. Faculty of Mining, Petroleum & Geophysics, Shahrood University of Technology, Shahrood, Iran
2. UiT The Arctic University of Norway, Tromsø, Norway
3. Faculty of Engineering, Østfold University College, Fredrikstad, Norway
Abstract
Production performance analysis plays a significant role in supporting the decision-making process, for managers and engineers dealing with the challenges of the optimization procedure of a system delivery capacity. Operational conditions can influence the production performance of a system drastically, in a short or long term, by affecting the system configuration, reliability, maintainability, maintenance supportability, and functional capacity of its components. Moreover, these impacts can lead to increased business risks and uncertainties. Such a situation demands the successful application of tools and methodologies to minimize the total business risk through an accurate prediction of production performance, addressing the effects of operational conditions. However, there is a lack of practical methodologies, for production performance analysis of systems operating under the time-dependent operational conditions. Hence, the central thrust of this article is to develop a systematic methodology, for the production performance analysis of a system considering the time-dependent operational conditions. In the case study, the results show that the production performance of mining equipment is affected significantly by the operational conditions. These changes occur across the working shifts and due to any changes in the production plan of the mine. The result of the analyses shows that the critical items in the mine is the loader. Hence, in order to increase the production performance of the system, the optimization of the reliability or maintainability of the loader needs to be considered as a priority. Moreover, the wagon drill has a significant excess capacity, which means that, by adding more trucks to the system, the production performance of the system can be improved.
Subject
Safety, Risk, Reliability and Quality
Cited by
6 articles.
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