Modelling of discrete downtime in continuous crushing operation

Crushing is a harsh process and production units are subjected to wear and failure over time which will reduce the overall performance of the plant. To achieve optimum process performance, both time dependant process dynamics and operating conditions should be taken into account. In this paper the aim is to simulate the process from a more operational perspective to evaluate process performance and process optimum for different operations. The objective is to model and simulate the discrete phenomena that can cause the process to alter performance and implement it with dynamic process simulations. An approach for combining discrete event simulations with time-dependent simulations for process evaluation and optimization is presented. The proposed approach demonstrates a systematic way to evaluate the process performance and locating optimum process configuration, for a given condition. The developed models can be used to optimize different aspects of the operation depending on the defined objective function and the system boundaries. Optimization of process throughput by manipulating configuration of both the grizzly and the crushers, as well as the time between calibrations has been illustrated in this paper. Adjusting the process continuously and calibrating it at the appropriate time can have major benefits when it comes to the process availability and utilization, increasing performance by 4.1-9.3% in these cases. Evaluation of process robustness and availability with regards to process specific factors and variation gave an indication of the process and unit performance under a long operating period. By combining discrete and dynamic simulation, a higher simulation fidelity can be achieved to provide a more operational perspective to the optimization and process analysis. (C) 2016 Elsevier Ltd. All rights reserved.