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

Autor:	Francisco Mata Cabrera, Issam Hanafi, Abdallah Jabbouri, Elena Beamud, Abdellatif Khamlichi
Rok vydání:	2010
Předmět:	Taguchi methods Fabrication Fuzzy rule Materials science Machining Design of experiments Ceramics and Composites Surface roughness Peek Composite material Condensed Matter Physics Fuzzy logic
Zdroj:	Journal of Thermoplastic Composite Materials. 24:399-413
ISSN:	1530-7980 0892-7057
DOI:	10.1177/0892705710391562
Popis:	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 Ra and Rt, 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%.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::7d2d450176fc83afee11ae1c75d3d928 https://doi.org/10.1177/0892705710391562 Zobrazit plný text záznamu