EWMA chart with curtailment for monitoring fraction nonconforming. Issue 4 (2nd October 2017)

• Record Type: Journal Article
• Authors: Haridy, Salah; Rahim, M. Abdur; Selim, Shokri Z.; Wu, Zhang; Benneyan, James C.
• Is Part Of: Quality technology & quantitative management. Volume 14:Issue 4(2017)
• Page Start: 412
• Page End: 428
• Publication Date: 2017-10-02
• Subjects: Control chart -- EWMA chart -- curtailment -- Rayleigh distribution -- average number of defectives; Quality control -- Periodicals; Quality control -- Statistical methods -- Periodicals; Industrial management -- Periodicals; Industrial management; Management -- Research -- Methodology -- Periodicals; Qualitative research -- Periodicals; Management; Quality control; Quality control -- Statistical methods; Periodicals; 658.00721
• DOI: 10.1080/16843703.2017.1304040
• Languages: English
• ISSNs: 1684-3703

Abstract

Abstract: The binomial Exponentially Weighted Moving Average (EWMA) control chart has been widely used as an effective tool for detecting small and moderate shifts in fraction nonconforming ( p ). This article presents a binomial EWMA chart employing a curtailment technique (abridged as Curt_EWMA chart) for monitoring p . The p shift is assumed to follow a Rayleigh distribution. It is found that the curtailment technique can improve the overall detection speed of the EWMA chart while maintaining the false alarm rate at a specified level. An algorithm is presented to find the optimal design of the Curt_EWMA chart. The results of the comparative study reveal that the Curt_EWMA chart outperforms the EWMA chart without curtailment by 41%, in terms of the average number of defectives, under different settings.