System Machine Selection in a Dry Grinding Process: Cost and Energy Savings

The dry grinding process (DGP) could be considered as a particular complex production system. Traditionally the design of this process has been based on heuristics. We attempt to find the nearest optimal design of a DGP choosing the model and number in every stage for the machines and buffers that can minimize investment and energy cost with a reasonable service level (SL). To solve the problem, a genetic algorithm and a simulation model to evaluate the SL along the time are proposed. The viability of the approach has been tested with three real cases and encouraging results have been obtained.