Review of Composite Machining and Related Optimization Techniques

This paper provides an inclusive review of literature, mostly from the past decade, on optimization techniques of composite materials machining, both conventional and non-conventional process. Composite materials are continually replacing conventional materials due to their excellent corrosion resistance, higher strength to weight ratio, but the machining of composites is a challenging process. Experimental trials notwithstanding, researchers have also used various optimization techniques such as Taguchi method, Genetic Algorithm, Simulated Algorithm, Response Surface Method, and Fuzzy Logic with ANOVA etc., to identify the optimal parameters for the machining processes. Also predictive modeling techniques such as Artificial Neural Networks and Finite Element Methods have also been employed as an optimization tools for studying the composite machining process. It was found that Taguchi method is the most preferred technique in the optimization studies.