An expert system for setting parameters in machining processes

• An expert system is proposed made of an integration of intelligent systems.
• Symbolic regression alpha beta is used instead of genetic programming.
• Statistical metrics are used to validate the models generated.
• A model is chosen considering complexity and minimization of error.
• Setting of parameters is made using the model in an evolutionary algorithms.

In this paper, an hybrid system is proposed for setting machining parameters from experimental data. A symbolic regression alpha–beta is used to build mathematical models. Every model is validated using statistical analysis then evolutionary computation is used to minimize or maximize the generated model. Symbolic regression α–β is used to build mathematical models by estimation of distribution algorithms. A practical case considering measured data of two machining process on three materials are used to illustrate the utility of the expert system because generates a set of parameters that improve the machining process.