Inverse prediction of critical parameters in orthogonal cutting using binary genetic algorithm

Abstract

An inverse problem is solved for concurrently assessing the rake angle, the chip thickness ratio and the required cutting width in an orthogonal cutting tool, when subjected to a prescribed force constraint. The force components which can be obtained experimentally by mounting either suitable dynamometers or force transducers on a machine tool, are calculated here by solving a forward problem. Due to inherent complexities involved in the calculations of the gradients, genetic algorithmbased evolutionary optimization algorithm is used in the present study. The results of the inverse problem have been compared with those of the forward problem. It is observed that a good estimation of the unknowns is possible. The current study is projected to be of use to decide on the relevant cutting tool parameters and adjusting the cutting process in such a manner that the cutting tool works within the dynamic limits.