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Abstract

Considering the increasing prospective regarding the various applications of Poly Ether Ether Ketone reinforced with 30% carbon fibres (PEEK CF30), there is a crucial need to investigate its machinability. In this work, focus is centered on non-linear regression based models that can be built to predict roug hness parameters R a and R t associated to turning of PEEK CF30 when using TiN coated cutting tool. Attention was paid to one-variant models that can be proposed to represent the effect of the cutting speed on the surface finish parameters. A broad class of non-linear interpolation models was considered. Their aptness to be used in modelling this particular application was assessed. The identification of the various mathematical models was performed by using experimental results that were obtained from CNC turning of PEEK samples. Based on statistical analysis, all the considered non-linear regression models proved to be highly significant and succeeded to fit adequately the experimental results.

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Abstract

Non-reinforced and reinforced Poly-Ether-Ether-Ketone (PEEK) plastics have excellent mechanical and thermal properties. Machining is an efficient process that can be used to manufacture specific mechanical parts made from PEEK composites. Researchers have focused on improving the performance of machining operations with the aim of minimizing costs and improving quality of manufactured products, in order to get the best surface roughness and the minimum cutting force. The parameters evaluated are the cutting speed, the depth of cut and the feed rate. In this paper, the effect of the mentioned parameters on surface roughness and cutting force, in dry turning of reinforced PEEK with 30% of carbon fibers (PEEK CF30) using TiN coated cutting tools, is analyzed through using robust design techniques such as Taguchi's design method, signal-to-noise (S/N) ratio and statistical analysis tools such as Pareto-ANOVA. The obtained results have shown that Taguchi method and Pareto ANOVA are suitable for optimizing the cutting parameters with the minimum possible number of experiments, and the optimized process parameters were determined for surface roughness and cutting force criteria.

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