Surface Roughness Minimization in Turning PEEK-CF30 Composites with TiN Cutting Tools Using Particle Swarm Optimization

Abstract

Poly ether ether ketone (PEEK) composite belongs to a group of high performance thermoplastic polymers and the addition of carbon fibers increases the resistance and rigidity of PEEK. Due to favorable mechanical and thermal properties and potential applications in various manufacturing industries, it is essential to analyze the machining performance of reinforced PEEK composites. The surface roughness is a widely used measure of product quality that could influence the performance of mechanical products and production costs. The present study establishes the relationships between the cutting conditions (cutting speed and feed rate) and three surface roughness parameters (centerline average surface roughness, maximum peak to valley height and root mean square roughness) by developing second order mathematical models based on response surface methodology (RSM). The reinforced PEEK with 30% of carbon fiber (PEEK-CF30) workpieces were machined using TiN-cutting tools. The experiments have been planned as per full factorial design of experiments (FFD). The developed surface roughness models were then employed with particle swarm optimization (PSO) to optimize the cutting conditions. PSO program gives the minimum values of surface roughness parameters and the corresponding optimal cutting conditions.