Multi-objective optimization in drilling of CFRP (polyester) composites: Application of a fuzzy embedded harmony search (HS) algorithm

Widespread application of carbon fiber reinforced polymer (CFRP) composites in automobile, structural and aerospace engineering leads to vital concern for attaining usable shapes with reasonable accuracy through machining and moulding processes. Machining of CFRP composites needs careful planning and estimation of adequate process parameters as it is substantially different from conventional machining of metallic materials. Performance characteristics in machining (drilling) of CFRP composites are greatly influenced by various process parameters such as drill speed, feed and drill diameter. Generally, thrust force, torque, surface roughness and delamination factor (both at entry and exit) are considered as the output performance characteristics in composite drilling. In the present work, the extent of process performance has been evaluated in drilling of CFRP composites using TiAlN coated solid carbide drill bit. Multiple performance characteristics are converted into an equivalent single performance characteristic known as Multi Performance Characteristic Index (MPCI) using a Fuzzy Inference System (FIS). A nonlinear regression model has been developed to express MPCI as a function of the selected process parameters. The regression model has been considered as the fitness function and finally optimized by a latest evolutionary technique known as harmony search (HS) algorithm which is inspired by the improvisation process of musicians. The effectiveness of the proposed algorithm has been compared with that of genetic algorithm (GA) as well as Taguchi's robust optimization philosophy. The results indicate that HS algorithm is quite efficient in searching optimal process parameters at less computational effort as compared to genetic algorithm due to diversity in search mechanism. (C) 2015 Elsevier Ltd. All rights reserved.