Authors: Shih-Chou Kao
Addresses: Department of Business Administration, Kao Yuan University, No.1821, Jhongshan Rd., Lujhu Dist., Kaohsiung City 821, Taiwan
Abstract: This study considers the construction of control charts when outliers could occur in the data. Simply increasing the width of control limits will make it more difficult to detect an out-of-control signal. This study aims to determine weights for each observation by measuring their respective distances to the average. The study proposes a retrospective weighted average and weighted inter-quartile range (WIQR) control chart based on the normal distribution that accounts for the false alarm rate, special causes, outliers, and a combination of special causes and outliers that might exist within the process. In addition to validating the detection effectiveness of the proposed control charts, this study also compares various average-type and range-type control charts for detecting the outliers and special causes. The proposed control charts show superior detection effectiveness in four tested scenarios compared to other types of control charts. Finally, the study also illustrates the practical application of the control charts for measuring the tensile strength of a deformed bar in coil. [Received 10 February 2014; Revised 21 August 2015; Revised 3 November 2015; Accepted 14 December 2015]
Keywords: inter-quartile range; IQR; normal distribution; outliers; robustness; retrospective weighted control charts; SPC; statistical process control; tensile strength; deformed bars; coil.
European Journal of Industrial Engineering, 2016 Vol.10 No.4, pp.407 - 430
Published online: 01 Aug 2016 *Full-text access for editors Access for subscribers Purchase this article Comment on this article