Statistical Monitoring and Optimization of Electrochemical Machining using Shewhart Charts and Response Surface Methodology

Abstract

The response surface methodology (RSM) and Shewhart control charts have been widely used in manufacturing to reduce variation, improve quality and optimize the output. This article proposes an application of individuals & moving range chart (I&MR) and RSM in electrochemical machining. The Shewhart-type I&MR control chart and RSM are combined together in an effective way to successfully guarantee the statistical control of the surface roughness (Ra) of the items produced by wire electrochemical turning, and meanwhile optimize Ra by exploring the optimal values of the machining parameters including applied voltage, wire feed rate, wire diameter, rotational speed and overlap distance. The conducted experiments reveal that the optimal values of the aforementioned factors are 23.67, 0.5, 0.2, 900 and 0.02, respectively.  A second-order regression model is also developed to predict the output (Ra) at different combinations of the input parameters. The developed regression model can predict the output values with a determination coefficient (R²) of 96.9%. The proposed combined scheme of Shewhart charts and RSM can be employed in other manufacturing processes and even in different service sectors to efficiently enhance the performance and reduce the cost.