Cost-effective supervisory control system in peripheral milling using HSM

A proposal for an intelligent monitoring and control system is introduced. Achievement of a specific surface roughness is the main goal because it is a well-known index of product quality and a technical requirement for mechanical products. The system integrates four modules: data acquisition, surface roughness monitoring, cutting tool monitoring, and intelligent process planning. Values of the cutting parameters for a peripheral milling process are estimated a priori, and by using a Genetic Algorithm, the optimal cutting parameters are determined. In intelligent process planning module, a Markov decision process is implemented to compute an optimal machining policy. Based on this policy, the system generates recommendations that optimize the operating costs.