Predictive Models for Different Roughness Parameters During Machining Process of Peek Composites Using Response Surface Methodology

Polyetheretherketone (PEEK) composite belongs to a group of high performance thermoplastic polymers and is widely used in structural components. To improve the mechanical and tribological properties, short fibers are added as reinforcement to the material. Due to its functional properties and potential applications, it’s impor- tant to investigate the machinability of non-reinforced PEEK (PEEK), PEEK rein- forced with 30% of carbon fibers (PEEK CF30), and reinforced PEEK with 30% glass fibers (PEEK GF30) to determine the optimal conditions for the manufacture of the parts. The present study establishes the relationship between the cutting con- ditions (cutting speed and feed rate) and the roughness (Ra , Rt , Rq , Rp ), by develop- ing second order mathematical models. The experiments were planned as per full factorial design of experiments and an analysis of variance has been performed to check the adequacy of the models. These state the adequacy of the derived models to obtain predictions for roughness parameters within ranges of parameters that have been investigated during the experiments. The experimental results show that the most influence of the cutting parameters is the feed rate, furthermore, proved that glass fiber reinforcements produce a worse machinability.