A review on machining and optimization of particle-reinforced metal matrix composites

Abstract

This paper offers a comprehensive literature review of the conventional machining processes along with optimization methods used in metal matrix composites (MMCs), such as turning, milling, drilling, and grinding machining processes. The tool wear mechanism and machinability of MMCs along with surface quality are discussed in the number of different manufacturing processes and examined thoroughly. Additionally, the manufacturing of MMC products through nonconventional machining processes such as electrical discharge machining (EDM), wire electrical discharge machining (WEDM), laser machining, electrochemical machining, ultra- sonic machining (USM), and high-speed machining are investigated and considered, in connection with MMC processing are discussed, as alternatives to the aforementioned processes. Moreover, this review focuses on the modeling of the machining process, finite element modeling, and simulation and optimization of soft computing methods in MMCs. The study will emphasize on the most generally used methods, namely, response surface methodology, artificial neural network, Taguchi method, and fuzzy logic as soft computing optimization methods. Finally, the comprehensive open issues and conclusions have drawn on the machining and optimization of particle-reinforced MMCs.