Mine Production Assurance Program- Development and Application

ssuring production forms a crucial part of mining business profitability. Factors related to various mine operations, activities and business processes can threaten required/planned mine production. To address problems and ensure production level in mining, it is necessary to implement a mine production assurance program (MPA). In order to propose a guideline and its component, this study started by reviewing four such techniques used in process industries. Comparing the tools, techniques and focus with mining productivity and production factors, it was observed that applicability of these methods for mining is limited due to lack of focus on equipment focus, cost focus and other parameters. Similarity of objectives and requirements of equipment focus lead to conclusion that PAP from oil and gas industry seems to be method which can guide MPA.\parAs a basis of MPA, an index is required to create a clear relationship between different situations which can occur in mining operation and production loss. A literature review on mining productivity improvement methods shows availability, utilisation and production performance of equipment are the key factors in determining overall production. A single index applicable for chain operation in mining is needed. A Mine Production index (MPi) is thus proposed. This index involves all three parameters for equipment productivity mentioned above. Weights associated with MPi calculation for bottleneck equipment can point out critical factors in equipment operation. Once bottleneck equipment and relevant critical factors are known, further analysis can be carried out to determine the possible causes of production loss. By using MPi for machine operations, it is possible to rank machines in terms of production effectiveness. When the study applied MPi to chain operations in a mining case study, a crusher was determined as bottleneck equipment.\parMining operation is heavily influenced by internal and external uncertainties. Operational uncertainties related to equipment includes its key factors leading to production i.e. availability, utilisation and performance. These factors are in turn dependent upon downtime, idle time, rated capacities. External parameters related to weather are based upon location of mining operation. Influence of these factors on production volume, could be used for better decision making during mining operations optimization. To effectively propose a method for correlating internal and externa