An Analysis of the Performance of the SPRT Chart with Estimated Parameters Under the Weibull Distribution

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

Most developments of the sequential probability ratio test (SPRT) control chart assume that the underlying process comes from a Normal distribution with known mean and standard deviation. Nevertheless, the true values of the process parameters are usually inaccessible in production settings, and they must be approximated from a set of Phase-I data. In certain areas, the process data can be positively skewed, which in turn affect the performance of control charts designed under the Normal distribution. In this paper, we provide a thorough analysis on the performances of the SPRT chart with estimated process parameters under the influence of Weibull distributed data. The unconditional properties of the expected value and standard deviation of the time to signal are evaluated using Monte Carlo simulation to facilitate comparisons between the Normal and Weibull distributions. Results show that both the in-control and out-of-control performances of the SPRT chart deteriorate when Weibull data are used. However, the optimal design of the SPRT chart with estimated process parameters seems to reverse the effect for large process mean shifts.

Original languageEnglish
Title of host publicationProceedings of the 12th International Conference on Robotics, Vision, Signal Processing and Power Applications
EditorsNur Syazreen Ahmad, Junita Mohamad-Saleh, Jiashen Teh
PublisherSpringer
Pages175-182
Number of pages8
ISBN (Electronic)9789819990054
ISBN (Print)9789819990047
DOIs
Publication statusPublished - 31 Mar 2024
Event12th International Conference on Robotics, Vision, Signal Processing, and Power Applications 2023 - Penang, Malaysia
Duration: 28 Aug 202329 Aug 2023

Publication series

NameLecture Notes in Electrical Engineering
Volume1123
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

Conference12th International Conference on Robotics, Vision, Signal Processing, and Power Applications 2023
Abbreviated titleROVISP 2023
Country/TerritoryMalaysia
CityPenang
Period28/08/2329/08/23

Keywords

  • Average time to signal
  • Process parameter estimation
  • Sequential probability ratio test
  • Statistical process control
  • Weibull distribution

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering

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