Multi objective optimization of process variables using grey relational analysis for drilling of hybrid composites (LM6/B4C/fly ash)

Abstract

Aluminium alloys continue to be an effective material for the aviation and automotive sectors in spite of the development of composites and other lightweight materials because of their sophisticated manufacturing techniques, strong durability against fatigue fracture propagation, and excellent impact endurance. As numerous holes are needed for creating rivets, drilling is the most difficult of all the machining operations. The primary problems with drilling these aluminium alloys are represented by a low hole quality, which increases the risk of airframe construction defects and lowers reliability. As a result, parts get discarded throughout the process of assembling, which affects the overall cost of production. To satisfy the needs of machined parts, the selection of Feed rate (F), Spindle Speed (S), Drill Material (D) and percentage of reinforcements (R) as well as drilling equipment, is necessary. The objective of this research work is to study the impact of cutting parameters on surface roughness (SR) and thrust force (TF) during drilling Hybrid MMCs, which were prepared by stir casting. The reinforcements used for fabrication were fly ash and boron carbide. A computer numerical control VMC with a cutting tool dynamometer for measuring TF was used for the experiments. The investigations used the L18 orthogonal array as their base of operation. The multi response optimization considering TF and SR was carried out using grey relational analysis (GRA) and the optimal level of cutting parameters like ‘F’, ‘S’, ‘D’ and ‘R’ were identified to obtain low TF and SR. The optimal machining parameters which give low TF and low SR are at 6 % reinforcement, coated carbide drill, S 3000 rpm and F 50 mm/min. Feed Rate (67.20 %) has the most significance on GRG trailed by S (15.88 %), Drill Material (6.39 %) and reinforcement percentage (3.65 %). Confirmation experiments demonstrated that grey relational analysis precisely optimized the process variables in drilling of hybrid MMCs.