Analysis and Optimization of Machining Process Parameters Using Design of Experiments

M. Naga Phani Sastry, K. Devaki Devi, K. Madhava Reddy

Abstract


In any machining process, apart from obtaining the accurate dimensions, achieving a good surface quality and maximized metal removal are also of utmost importance. A machining process involves many process parameters which directly or indirectly influence the surface roughness and metal removal rate of the product in common. Surface roughness and metal removal in turning process are varied due to various parameters of which feed, speed, depth of cut are important ones. A precise knowledge of these optimum parameters would facilitate reduce the machining costs and improve product quality. Extensive study has been conducted in the past to optimize the process parameters in any machining process to have the best product. Current investigation on turning process is a Response Surface Methodology applied on the most effective process parameters i.e. feed, cutting speed and depth of cut while machining Aluminium alloy and resin as the two types of work pieces with HSS cutting tool. The main effects (independent parameters), quadratic effects (square of the independent variables), and interaction effects of the variables have been considered separately to build best subset of the model. Three levels of the feed, three levels of speed, three values of the depth of cut, two different types of work materials have been used to generate a total 20 readings in a single set. After having the data from the experiments, the performance measures surface roughness (Ra) of the test samples was taken on a profilometer and MRR is calculated using the existing formulae. To analyze the data set, statistical tool DESIGN EXPERT-8 (Software) has been used to reduce the manipulation and help to arrive at proper improvement plan of the Manufacturing process & Techniques. Hypothesis testing was also done to check the goodness of fit of the data. A comparison between the observed and predicted data was made, which shows a close relationship.

Key words: Surface Roughness and Metal Removal Rate, Turning, Response Surface    Methodology, Aluminium Alloy, Resin.

 


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ISSN (Paper)2224-6096 ISSN (Online)2225-0581

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