A Simulation-based Search Technique for Determination of Process Parameters with Stochastic Tool Lives

This paper presents a simulation-based search approach for the machining economics problem with stochastically distributed tool lives. It is evident that the life of cutting tools used in machining centers is modeled using proper probabilistic methods due to the stochastic nature of tool wear data. This makes the machining economic problem more complex and difficult to solve using deterministic optimization methods. Therefore, simulation could be the only possible way to solve this stochastic problem, as presented in this work. The objective it to find the process parameters (speed and feed) that minimize the total production cost per piece. Numerical examples are presented to demonstrate and validate the proposed approach