RAM analysis of mining equipment and framework for data collection

Abstract

In the mining industry, equipment are continuously increasing in size and complexity. At the same time, the demand for available plants and continuous production has never been higher. The performance of equipment depends on the reliability and maintainability performance of the equipment along with the maintenance supportability, operational conditions, and environmental conditions. In order to improve plant availability, fully utilize equipment performance, avoid equipment breakdowns and optimize operation and maintenance (O&M), the concept of reliability, availability and maintainability (RAM) analysis is required. In most industries, the only collected explanatory variables used in RAM analysis have been time to failure (TTF) and time to repair (TTR). For a more precise estimation of the reliability and maintainability characteristics of mining equipment, factors influencing the reliability and maintainability of equipment should be collected and included in the analysis.

In this thesis, the concept of RAM analysis is applied for availability improvement in the mining industry as a quantitative case study. Furthermore, a framework for data collection including influence factors has been developed, which highlights important steps in the data collection process. For including the effects of influence factors in RAM analysis, the Proportional Hazard Model (PHM) with the modified Proportional Repair Model (PRM) are discussed. Finally, a qualitative case study is conducted to demonstrate the application of the framework for data collection for RAM analysis.

The result of the RAM analysis have been used to determine optimum preventive maintenance interval in order to improve availability performance. Furthermore, aspects for improvement of reliability performance and maintainability performance have been assessed in order to improve overall system availability. The framework developed for data collection is considered general enough to cover several industries. However, the framework is especially suited for the mining industry with the use of the PHM and PRM for including influence factors in reliability and maintainability analysis. The work in this thesis, the framework for data collection especially, is considered valuable and necessary as it addresses an area that has received less focus in today's mining industry.

Keywords: RAM, mining, O&M optimization, data collection, influence factors, Proportional hazard model, Proportional repair model