Optimal process design using soft computing approaches

This paper proposes an optimal process design by using soft computing approaches. The proposed procedure integrates the Taguchi method, the artificial neural network, and the genetic algorithm. The Taguchi method is applied to collect experimental data representing the quality performances of a system. The artificial neural network is used to build a system model. The genetic algorithm is employed to search for the optimal process parameters. A process parameters design for a titanium dioxide (TiO₂) thin film of the vacuum sputtering process is studied in this paper. The result estimated from the system model of the proposed procedure is satisfactory.