SIMULTANEOUS OPTIMIZATION OF ROBUST DESIGN WITH QUANTITATIVE AND ORDINAL DATA

摘要

Many industries have employed the Taguchi method over the years to improve product or process performance. A real problem in a product or process usually has multiple quality characteristics. In confronting a product or process with multiple quality characteristics, it is difficult to determine the optimal control factor settings for each of the quality characteristics, as each usually varies according to different combinations of control factor settings. Several studies have presented approaches optimizing the multiple quantitative quality characteristics design. Due to the inherent nature of the quality characteristic or the convenience of the measurement technique and cost-effectiveness, the data observed in many experiments are ordinal data. Few published articles have focused primarily on optimizing the multiple quality characteristics involving quantitative and ordinal data. This paper presents a simple approach to optimizing this problem based on the quality loss function. A numerical example of the polysilicon deposition process for minimizing surface defects and achieving the target thickness in a very large-scale integrated circuit can demonstrate the proposed approach's effectiveness.