Modeling system error in batch machining based on genetic algorithms

During batch machining under a static cutting-tool setting, machining errors of workpieces always have an ascending trend with the order of workpieces. Here the error trend is called the system error in batch machining. To compensate for the machining system error and enhance machining accuracy, modeling the system error is the key process. This paper first analyses several popular modeling methods and identifies their deficiencies when used in system error modeling. Subsequently, a new method of system error modeling based on Genetic Algorithms (GA) is introduced. Finally, a real-life application example using the new method and a comparison with other modeling methods are given, which indicate that the proposed GA based method is good. The paper also points out the essence that the proposed modeling method is a polynomial regression one in a broad sense, and is useful in the modeling of non-uniform error series.