Parametric optimization in drilling of GFRP composites using desirability function integrated simulated annealing approach. (2021)

• Record Type: Journal Article
• Authors: Nayak, Bijaya Bijeta; Kundu, Souranil; Kumar, Mritunjay; Kumar, Vivek; Kumar, Rishabh; Shivam, Kumar Poornendu
• Is Part Of: Materials today. Volume 44:Part 1(2021)
• Page Start: 1983
• Page End: 1987
• Publication Date: 2021
• Subjects: GFRP composites -- Desirability function approach -- Simulated annealing -- Drilling; Materials science -- Congresses -- Periodicals; 620.1
• DOI: 10.1016/j.matpr.2020.12.116
• Languages: English
• ISSNs: 2214-7853

Abstract

Abstract: The present work focuses on parametric optimization during drilling of glass fibre reinforced polymer (GFRP) composites. GFRP composites have wide range of applications in the field of aerospace, defence, automobile and transportation industries. Drilling process is broadly used for GFRP composites since components made out from GFRP composites are usually near net shaped, thus requiring holes for assembly integration. Hence proper selection of process parameters during drilling of GFRP composites is essential. In order to study delamination in GFRP at entry and exit side of the laminate and surface roughness, experiments have been conducted using Taguchi's experimental design with a view to reduce number of experimental runs. Cutting speed, feed rate and drill size are considered as three input parameters for drilling at four different levels. Drilling of GFRP is performed using a CNC milling machine under prefixed conditions. Taguchi's approach fails to solve multi-response optimization problem. Therefore, desirability function approach is used to convert multi response into equivalent single response. Regression analysis has been used to develop the relationship between composite desirability index and input parameters, resulting a valid mathematical model. Finally, simulated algorithm is used to obtain the optimum parameter setting.