| Summary: | Two different materials subjected to machining can behave differently when cutting them with the same tool, at the same cutting speed and feed rates, using the same machine, and working under similar condition. Some may produce long curly chips (like mild steel); some may produce short chips (like cast iron); some may get a smooth finish; some may end up with a rough urface; some may produce chatter and some may produce lots of heat and quickly blunt the tool. The use of advanced materials which are commonly composed of carbon fibre, polimers and metal has increased due to their special mechanical and physical properties such as in the aeronautical, aerospace, automotive, biomechanical, mechanical and other industrie . As a re ult of the e properties and potential applications, there exists an urgent need to understand questions associated with the machinability of these materials. Obviously, for Carbon Fibre Reinforced Plastic with Aluminum grade 2024 (CFRP/AI2024) composites material, integrating into one single machining operation has proved to be more challenging due to the anisotropic and non-homogeneou tructure ofCFRP and ductile nature of Aluminum. This introduces several types of damage like matrix cracking and thermal alterations, fiber pullout and fuzzing during drilling and trimming which affect the quality f machined surface. Many of these problems occured due to inappropriate use ofvari u cutting tool designs materials and cutting parameters. The research project aims to study and model machined surface quality of CFRP/AI2024 using Two Level Full Factorial Design experiment. This research project has three objective. First, to perform the trimming process using down milling. Second, to statistically and graphically analyze the influence and interaction of cutting parameters. Third, to optimize cutting parameters in order to get the surface texture quality ofCFRP/AI2024 to les than 111m. The trimming process was carried out via down milling on a stack of multidirectional CFRPI A12024. Three cutting parameters were considered namely, spindle speed (N), feed rate ([r) and depth of cut (de). Two level full factorial design was utilized to plan systematic experimental methodology. The analysis of variance (ANOY A) wa used to analyze the influence and the interaction factors associated to surface quality. The results showed that the depth of cut is the most significant factor for A12024, and for CFRP the spindle speed and feed rate are significant. The validation test showed average deviation of predicted to actual value urface roughness is 3.11 % for CFRP and 3.43% for A12024. Optimization of surface roughness for CFRP/AI2024 of below that I urn can be obtained at the setting of N = 11750 rpm, fr = 750 mm/min and = 0.255 mm respectively.
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