Measurement and optimization of multi-attribute characteristics in milling epoxy granite composites using rsm and combined ahp-topsis

Abstract

Epoxy granite composites with its wide range of applications in machine tool industries are manufactured by molding process and require post cast machining operations to meet the desired dimensional accuracy for assembly of machine tool structures. In this research work, milling of epoxy granite composites are carried out based on the experimental design from Response Surface Methodology (RSM) techniques and further the optimal solutions are determined by a novel hybrid algorithm AHP-TOPSIS. Central Composite Design (CCD) model is applied with three factors-three levels and the measured output responses are thrust force, tangential force and surface roughness. Experimental combinations of 20 different trials are performed using high speed steel end mill cutter of diameter 10 mm with three levels of input parameters: speed; fibre content and feed rate at a uniform depth of cut. The relative importance matrix formulated proved to be highly consistent with its consistency ratio to a maximum of 0.000641 which lies below the higher range of 0.1. Consistency ratio of 0.000641 reveals that the optimal solutions determined will be highly reliable and the decision making is much more judicious. Optimal solution determined from hybrid AHP-TOPSIS methods are: speed 1800 rpm; feed rate 0.03 m min−1 and 0% percent fibre content. Functional relationships among parameters and responses established by RSM are consistent upto 95% and its significance is tested by analysis of variance. Comparison among predicted and experimental values of three measured responses convey that the percentage variations are minimum with up to 2.03% for surface roughness, 2.50% for thrust force and 2.71% for tangential force components. This research work provides a systematic procedure and clear framework for determination of optimal machining conditions by hybrid methodology on the basis of technique for order preference by similarity to ideal solution (TOPSIS) combined with analytical hierarchy procedure (AHP) for attribute weights and further analyzes the influence of machining parameters over measured responses.