GA based optimization of process parameters for drilling on Al-MgO metal matrix composite

Abstract

Metal matrix composites are displaying high potential characteristics as aerospace, automobile, defence, and research industries’ materials. Among the various types, aluminum based composites find increasing demands due to light weight property along with greater mechanical strength. These materials are used in fabrication of structural components, in assembly and manufacturing sectors, which are joined or assembled after the drilling process. Drilling process easily facilitates the assembly of these composites and provides high surface finish simultaneously. The paper investigates the optimization of the drilling parameters with multiple performance characteristics of aluminum based composite Al-MgO. The metal matrix composite was fabricated by the stir casting process. It was reinforced with the magnesium oxide (MgO) while the base matrix was 5052 aluminium. This prepared material was used for the investigation of drilling parameters. The process parameters were selected based on research work and the machine configuration. These were spindle speed, feed rate and drill diameter. A mathematical model was proposed for analysis of effect of various drilling process parameters. These were further optimized, through a modern optimization technique i.e. genetic algorithm, based on multiple performance characteristics which included temperature, dimensional accuracy and burr height (exit). The result concluded the analysis by identifying the most significant factors that affect the drilling of aluminum based composite.