Process Quality Evaluation Model with Taguchi Cost Loss Index

Abstract

Process Capability Indices (PCIs) are not only a good communication tools between sales departments and customers but also convenient tools for internal engineers to evaluate and analyze process capabilities of products. Many statisticians and process engineers are dedicated to research on process capability indices, among which the Taguchi cost loss index can reflect both the process yield and process cost loss at the same time. Therefore, in this study the Taguchi cost loss index was used to propose a novel process quality evaluation model. After the process was stabilized, a process capability evaluation was carried out. This study used Boole’s inequality and DeMorgan’s theorem to derive the (1−α)×100% confidence region of (δ,γ2) based on control chart data. The study adopted the mathematical programming method to find the (1−α)×100% confidence interval of the Taguchi cost loss index then employed a (1−α)×100% confidence interval to perform statistical testing and to determine whether the process needed improvement.

Keywords

• process capability indices
• Taguchi cost loss index
• confidence interval
• mathematical programming
• control chart data