Modeling of TiN Coating Grain Size Using RSM Approach

Abstract

Modeling of thin film coating is an important work to identify the required characteristic. In general, suitable coating process parameters are very important to find the best characteristics of coating and towards less material usage, reduced trial in experiment and less machine maintenance. In this paper, Response Surface Methodology (RSM) was implemented in modeling TiN coating grain size. N2 pressure, Argon pressure, and turntable speed were selected as process variables, while the coating grain size as an output response. Significant factors that influence the coating characteristic are determined by using Analysis of Variance (ANOVA) and to develop a polynomial quadratic model. Findings from this study suggested that turntable speed and Argon pressure quadratic term has significant effect to the TiN coating grain size. The result also showed that the actual validation data fell within the 95% prediction interval (PI) and the residual errors percentage was lower than 10%.