Process improvement methodology based on multivariate statistical analysis methods

Abstract

A systematic procedure for process improvement methodology is proposed based on multivariate statistical process control methods. To take advantage of a large amount of historical data, the procedure employs a combination of hierarchical clustering method and statistical process control methods to detect and analyze the key factors that significantly affect the performance of processes. This methodology consists of four sequential steps: (1) Data collection and multivariate statistical analysis; (2) hierarchical clustering and operation mode detection; (3) selection of dominant variables; (4) a new operational guideline and its validation. The proposed procedure was applied to improve the heat efficiency of an industrial hot stove system located at Pohang Iron & Steel Co. (POSCO) in Korea. The implementation results show that the proposed methodology helps us systematically improve the operating conditions of the hot stove system.