Optimization of Cutting Parameters for Turning Process using Genetic Algorithm
This paper provides a advanced technique for quality improvement in turning operations. The main objective of this paper is to find the optimal cutting parameters in turning operations. The orthogonal array, the signal-to-noise ratio, and the analysis of variance are employed to study the performance characteristics in turning operations of AISI 1030 steel bars using TiN coated tools. The model was developed initially for unidiameter case and then adapted to other workpiece geometries. An Adaptive Neuro Fuzzy Inference System (ANFIS) is proposed in this paper to control a constant cutting force turning process under various cutting conditions. The ANFIS consists of two parts: predictor and the fuzzy logic controller.