Title: Optimisation of drilling parameters for minimum circularity error in FRP composite

Authors: Rajkumar Tibadia; Koustubh Patwardhan; Dhrumil Patel; Dinesh Shinde; Rakesh Chaudhari

Addresses: SVKM's Narsee Monjee Institute of Management Studies (Deemed to be University), Mukesh Patel School of Technology Management and Engineering, Shirpur, Dist- Dhule, MS, India ' SVKM's Narsee Monjee Institute of Management Studies (Deemed to be University), Mukesh Patel School of Technology Management and Engineering, Shirpur, Dist- Dhule, MS, India ' SVKM's Narsee Monjee Institute of Management Studies (Deemed to be University), Mukesh Patel School of Technology Management and Engineering, Shirpur, Dist- Dhule, MS, India ' SVKM's Narsee Monjee Institute of Management Studies (Deemed to be University), Mukesh Patel School of Technology Management and Engineering, Shirpur, Dist- Dhule, MS, India ' SVKM's Narsee Monjee Institute of Management Studies (Deemed to be University), Mukesh Patel School of Technology Management and Engineering, Shirpur, Dist- Dhule, MS, India

Abstract: In composite materials, the damage is characterised by the delamination and circularity error of drilled holes. The amount of delamination and circularity error depends on different machining parameters such as spindle speed, feed Rate, and plate thickness. The present paper attempts to investigate an optimal combination of process parameters for drilling of composite laminates. The work is carried out on industrial grade FRP composite laminates with varying process parameters. The experiments are designed using a 'Box-Behnken design', grounded in the response surface methodology. Circularity error is considered as the output response as it is prominent in the drilling of composite laminates. ANOVA test is carried out to find the significance of the input parameters and test the empirical model. The effect of input parameters on the amount of circularity error is also investigated. Genetic algorithm (GA) and particle swarm optimisation (PSO) is used to predict the optimal settings of input machining parameters.

Keywords: Box-Behnken design; BBD; FRP composite; response surface methodology; RSM; genetic algorithm; particle swarm optimisation; PSO.

DOI: 10.1504/IJMATEI.2019.103608

International Journal of Materials Engineering Innovation, 2019 Vol.10 No.4, pp.271 - 285

Received: 23 Jan 2019
Accepted: 26 Apr 2019
Published online: 13 Nov 2019 *

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