Fuzzy Logic-Based Modeling of Surface Roughness Parameters for CNC Turning of PEEK CF30 by TiN-Coated Cutting Tools

Abstract

An important range of existing engineered industrial parts consists of plastic materials that are reinforced with carbon fibers. Due to their excellent mechanical and thermal properties, machined mechanical parts made from reinforced polyetheretherketone (PEEK) composite materials have become standard in many high-technology engineering fields such as aerospace, automotive, and electronics. There is however a crucial need to predict the machining criteria for reinforced PEEK composite materials in order to optimize their fabrication process. In this article, the process parameters including cutting speed, feed rate, and depth of cut are investigated. A fuzzy rule-based model was derived to predict the surface roughness parameters R_a and R_t, in dry turning of reinforced PEEK with 30% of carbon fibers using TiN-coated cutting tools. The model was identified using results of experiments carried out according to Taguchi method. Predictions of the fuzzy-based model were found to fit, very well, experimental data with a correlation coefficient as high as 99%.

Keywords

turning surface roughness PEEK CF30 TiN-coated cutting tool fuzzy logic design of experiment.

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