A Study on the Performances of the SPRT Control Chart When Estimating Process Parameters

Jing Wei Teoh*, Wei Lin Teoh, Laila El-Ghandour, Zhi Lin Chong, Sin Yin Teh

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The sequential-probability-ratio-test (SPRT) control chart is well-known for its outstanding detection ability towards a wide range of process mean shifts. In the existing literature, the SPRT chart has been regularly designed from the standpoint that the process parameters are known. Nonetheless, industrial practitioners reveal that these process parameters are hardly known. They often estimate these process parameters using a modest number of Phase-I samples. This in turn leads to different outcomes obtained across practitioners. In this paper, we present detailed insights about the distribution of the conditional ATS when the process parameters are estimated. Also, some statistical properties of the ATS through Monte Carlo simulation are presented in this paper. Particularly, the standard deviation of the ATS is examined in this paper to evaluate the practitioner-to-practitioner variability. Results show that a large Phase-I sample, and a large desired maximum mean shift in optimization design, are required to reduce volatilities in the average and standard deviation of the ATS values. Finally, we provide recommendations for the Phase-I sample sizes tailored to specific objectives of the SPRT chart when the process parameters are estimated.

Original languageEnglish
Title of host publicationProceedings of the 9th International Conference on Computational Science and Technology. ICCST 2022
EditorsDae-Ki Kang, Rayner Alfred, Zamhar Iswandono Bin Awang Ismail, Aslina Baharum, Vinesh Thiruchelvam
PublisherSpringer
Pages449-463
Number of pages15
ISBN (Electronic)9789811984068
ISBN (Print)9789811984051
DOIs
Publication statusPublished - 27 Apr 2023
Event9th International Conference on Computational Science and Technology 2022 - Johor Bahru, Malaysia
Duration: 27 Aug 202228 Aug 2022

Publication series

NameLecture Notes in Electrical Engineering
Volume983
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

Conference9th International Conference on Computational Science and Technology 2022
Abbreviated titleICCST 2022
Country/TerritoryMalaysia
CityJohor Bahru
Period27/08/2228/08/22

Keywords

  • Average time to signal
  • Estimated parameters
  • Quality control
  • SPRT control chart
  • Standard deviation of the average time to signal

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering

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