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Productivity management in materials handling is critical to mining operations. Most open pit mines use modular dispatch systems to control and monitor the movement of their materials handling equipment and operations. Statistical methods can be used on the data collected by the dispatch systems to identify major losses in time, tonnage and finances in productivity management. In this study, three ranking methods (a base case and two modified ranking methods) were used to evaluate the significance of the deviation and correlation parameters in productivity losses. A load and haul productivity loss ranking model was developed using data obtained from Mempeasem Gold Mine’s from January to October 2018 and tested with data obtained in November 2018. The results show that the ranking model can be used in the analysis of production data over any period of time and that the model is applicable in the analysis of the performance of all types of discrete load and haul equipment (trucks and excavators), either operating individually or in combination. The ranking based on deviation values is useful for comparative purposes. However, the ranking based on reduced values is more useful in decision making processes as it enables mine operators to take mitigation measures according to the level of priority of each item. Decision makers could also use the suggested colour coding for easy identification of the priority losses.

Evaluating Productivity Management of Materials Handling System at Mempeasem Gold Mine