Author(s)

SORAYA ZENHARI

Abstract

On five axis machines, it is necessary to compensate for position independent geometric errors (and position dependent geometric errors) to enhance machining precision. The purpose of this paper is to present an inverse kinematic model which provides clear solutions when executing motion commands according to an inverse kinematic model. A quantum hybrid genetic algorithm is used to determine the parameters of the kinematic model to achieve the most optimal performance possible. A different simulation result validated the proposed approach. This results in an 80% improvement in accuracy compared to conventional genetic algorithms with similar parameters, along with faster convergence. The model is versatile and can be used in a wide range of machine tools, especially those with rotary axes that are not orthogonal. The proposed algorithm can easily be adapted for use in computer-aided design and computer-aided manufacturing systems, depending on the machine’s maximum range of motion.

Keywords

screw theory, five axis machine tool, hybrid genetic algorithm, error compensation