Multi-Response Optimization in Drilling of Composites: Introduction of a Similarity Based Approach in Combination with Taguchi's Philosophy

Abstract

AbstractIn recent years, the application of polymer composites has been enormously increased particularly in aerospace as well as in automobile sector due to its light weight, high specific stiffness and high specific strength. Machining of those composites has really become an emerging area of research. A considerable volume of research has already been carried out by the pioneers in order to study machining and machinability aspects of these composites, thereby, maintaining both product quality as well as productivity. Drilling is considered as one of the most common machining processes for assembly of composites. In case of fiber reinforced polymer (FRP) composites, delamination and fiber pull out are the major problems that arise during drilling operations. Defect free drilling whilst ensuring satisfactory machining performance (in terms of quality as well as productivity) is definitely a challenging task. In this context, the present study mainly attempts to reduce drilling induced damages and at the same time to improve machining performances during drilling of polymer composites by determining an optimal parametric combination in view of multiple process responses and by considering effects of drilling process control parameters, drill geometry (diameter of drill bit) as well as composite type. Attempt has also been made to understand the relationship (influence) between input-output(s); where, inputs i.e. process parameters have been considered like composite type, drill speed, feed rate, drill diameter and outputs have been and drilling responses like thrust force, torque, delamination at entry and exit and average surface roughness of the drilled hole. Multi-response optimization has been performed using Deng's similarity based method in combination with Taguchi's optimization philosophy. Results obtained thereof have been compared with TOPSIS (Technique for Order Preference by Similarity to Ideal Solution)-based Taguchi approach.