Multidisciplinary optimization of etch process chamber on the basis of MCDM

Abstract

A multidisciplinary optimization integrating flow and plasma performance was used to develop an etch process chamber with dualfrequency capacitively coupled plasma. Pressure and ion density characteristics are significantly influenced by structures, such as electrode gap, number of confinement rings, electrode radius, and process conditions of flow rate. This study aims to minimize the objective functions of pressure and ion density simultaneously. Based on flow and plasma simulation, an approximation model is created using quartic response surface method (RSM). A genetic algorithm was utilized to explore Pareto front. The concept of entropy weight is combined with the weight defined in analytic hierarchy process to create a synthetic weight over the objectives. The non-dominated solutions are ranked by the modified technique for order preference by similarity to ideal solution. The ranking list helps arrive at rational decisions and provide a unique solution. The optimum structure of the chamber is obtained and the final solution is discussed. The proposed optimization framework improves the distribution profile of pressure and ion density.