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