Analysis and Optimization of Machining Process Parameters Using Design of Experiments

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.

STATISTICAL APPROACH FOR MULTI CRITERIA OPTIMIZATION OF CUTTING PARAMETERS OF TURNING ON HEAT TREATED BERYLLIUM COPPER ALLOY

In machining operations, achieving desired performance features of the machined product, is really a challenging job. Because, these quality features are highly correlated and are expected to be influenced directly or indirectly by the direct effect of process parameters or their interactive effects. This paper presents effective method and to determine optimal machining parameters in a turning operation on heat treated Beryllium copper alloy to minimize the surface roughness, cutting forces and work tool interface temperature along with the maximization of metal removal rate. The scope of this work is extended to Multi Objective Optimization. Response Surface Methodology is opted for preparing the design matrix, generating ANOVA, and optimization. A powerful model would be obtained with high accuracy to analyse the effect of each parameter on the output. The input parameters considered in this work are cutting speed, feed, depth of cut, work material (Annealed and Hardened) and tool material (CBN and HSS)