Investigation on the Turning Parameters for Surface Roughness using Taguchi Analysis

One of the important interests in the machining is attaining better surface roughness as well as dimensional accuracy. Polymer materials are continuously displacing the conventional materials. Their machining behavior is different in many aspects from machining of conventional metallic materials. Polymer based composite materials have superior properties for mechanical strength and stiffness, such as high strength-to-weight ratio and high stiffness-to-weight ratio. Fiber reinforced polymer composite materials are the one which are produced closer to the required shape, further machining is often necessary to achieve expected surface characteristics. This experimental study targets the machining of carbon fiber reinforced polymer material made into the form of tube. It examines various process parameters such as cutting speed, feed and depth of cut and their importance in deciding the surface roughness. Surface roughness was measured after machining is carried out under specified machining conditions. This experimental study focuses on the prediction of machining parameters that yield better surface characteristics in order to avoid machining of hard materials such as fiber reinforced composite materials so that enormous money spent in machining could be saved to some extent. For prediction this experimental study makes use of response surface methodology. The Taguchi method is used to solve many engineering problems. This work uses the Taguchi's orthogonal array method to find out the number of experiments to be carried out for turning operations. Also the analysis of variance is used to investigate the cutting parameters. In addition to the optimal cutting parameters for turning operations, the main cutting parameter that affect the cutting performance in turning operations could be found out.

Presented in Chemical, Civil and Mechanical Engineering Tracks of 3rd Nirma University International Conference on Engineering (NUiCONE2012).