Influence of Data Collection and Conditioning Strategies on the Significancy of Performance Indices in Mineral Processing Plants

The optimisation of mineral processing plants requires the evaluation of performance indices such as production rate, product quality, valuable mineral recovery and process efficiency. Decision to change operating conditions or equipment to improve plant performances rely on the significancy of the estimated performance indices. The better is the quality of the estimation, the better is the discrimination capability of the index and as a consequence the larger is the operation improvement. The reliability of performance calculation depends on the sensors nature, accuracy and location, on the data redundancy, on the correction method applied to raw data and finally on the propagation of measurement errors along the calculation of performance indices. To maximize the quality of the data collected for performance evaluation, the following techniques are presented, discussed and illustrated: redundancy and observability analysis, data filtering for mass conservation, variance analysis of performance calculation, and data acquisition strategy design.