Multi-Response Optimization of Input Parameters in End Milling of Metal Matrix Composite Using TOPSIS Algorithm

Abstract

Automobile and aerospace industries extensively use Aluminium Metal Matrix Composite (MMCs). MMCs have high strength and excellent corrosive-resistant properties. MMCs are considered to be very difficult-to-machine materials due to the intermittent nature of the reinforcements, which resulted in tool wear and edge breaking. To overcome these machining issues, carbide tool is an attractive mode to perform machining on this kind of material. This chapter presents the determination of the optimal machining parameter setting, which will lead to maximum material removal rate (MRR) and minimum surface roughness (Ra) in milling of aluminium LM24 reinforced with 2 wt.% of Boron carbide (B4C) metal matrix composite. The MMC is cast by ultrasonic-assisted stir casting technique. Experimentation was performed for three machining parameters of milling, namely speed, feed and depth of cut (DOC). The mathematical models for output characteristics as Ra and MRR have been developed by means of response surface methodology (RSM). End milling operation was performed on automatic vertical milling machine SV-2E using carbide tool cutter. The “Technique for order of preference by similarity to an ideal solution” (TOPSIS) algorithm was utilized to optimize multiple objective problems of machining characteristics. The influence of individual machining parameter on MRR and Ra was studied. DOC has a significant influence on Ra. It was found that the Ra is very sensitive to DOC and speed. MRR is sensitive to DOC and feed.