Capability performance analysis for processes with multiple characteristics using accuracy and precision

Process capability indices have been widely used in the manufacturing industry to provide numerical measures for process potential and process performance. However, from the perspective of improving process quality, there is a significant amount of process information that cannot be conveyed with a single index. Therefore, a single index does not have the ability to represent distinct problems in process performance or to provide the production department with sufficient information to make improvements. Thus, we applied an accuracy index δ and a precision index γ capable of reflecting the degree of deviation from target values and the degree of variance and incorporated the quality-level concept of the six-sigma model to develop a process quality-level analysis chart capable of analyzing the process capabilities of multiple quality characteristics. In addition to being able to directly identify the quality levels for various quality characteristics, the process quality-level analysis chart also provides recommendations for improvement of all quality-level regions to serve as a reference for production departments. Mathematical programming was used to develop a statistical hypothesis testing model to assist production departments in confirming the effectiveness of implemented improvements. This was achieved through derivation of a joint confidence interval for δ and γ from Boole’s inequality. From this, we obtained the upper and lower limits of the ( 1 − α ) × 100 % for δ and γ . Finally, we also applied the proposed approach to a case study of a five-way pipe process.