2016
DOI: 10.1002/qre.2042
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CUSUM Schemes for Monitoring Prespecified Changes in Linear Profiles

Abstract: Because of the characteristics of a system or process, several prespecified changes may happen in some statistical process control applications. Thus, one possible and challenging problem in profile monitoring is detecting changes away from the ‘normal’ profile toward one of several prespecified ‘bad’ profiles. In this article, to monitor the prespecified changes in linear profiles, two two‐sided cumulative sum (CUSUM) schemes are proposed based on Student's t‐statistic, which use two separate statistics and a… Show more

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Cited by 13 publications
(10 citation statements)
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“…The above simulations results, for both control charts (C_MEWMA and B_MEWMA), were obtained under the assumption that the true profile parameters (eg, B and Σ ε ) are known. This has been a common assumption in most of the related studies; see, for example, Abbas et al, [48][49][50] Eyvazian et al, 40 Kamranrad and Amiri, 14 Kazemzadeh et al, 15 Khedmati and Niaki, 16 Chiang et al, 17 and Zhang et al 18 Following those earlier works, we obtained only one UCL value for the classical approach (see Table 1). We then considered different values of m to monitor this effect on the detection performance of the Bayesian control chart.…”
Section: Comparison Study (Classical Vs Bayesian Mewma Control Chart)supporting
confidence: 75%
See 3 more Smart Citations
“…The above simulations results, for both control charts (C_MEWMA and B_MEWMA), were obtained under the assumption that the true profile parameters (eg, B and Σ ε ) are known. This has been a common assumption in most of the related studies; see, for example, Abbas et al, [48][49][50] Eyvazian et al, 40 Kamranrad and Amiri, 14 Kazemzadeh et al, 15 Khedmati and Niaki, 16 Chiang et al, 17 and Zhang et al 18 Following those earlier works, we obtained only one UCL value for the classical approach (see Table 1). We then considered different values of m to monitor this effect on the detection performance of the Bayesian control chart.…”
Section: Comparison Study (Classical Vs Bayesian Mewma Control Chart)supporting
confidence: 75%
“…The above simulations results, for both control charts (C_MEWMA and B_MEWMA), were obtained under the assumption that the true profile parameters (eg, B and Σ ε ) are known. This has been a common assumption in most of the related studies; see, for example, Abbas et al, Eyvazian et al, Kamranrad and Amiri, Kazemzadeh et al, Khedmati and Niaki, Chiang et al, and Zhang et al…”
Section: Comparison Study (Classical Vs Bayesian Mewma Control Chart)mentioning
confidence: 80%
See 2 more Smart Citations
“…The assumption is widely used in Phase II process control. Related works include Kim et al, 6 Zou et al, 7 Saghaei et al, 8 Li and Wang, 9 Mahmoud et al, 10 Eyvazian et al, 11 Chen and Nembhard, 12 Mahmoud, 13 Xu et al, 14 Xu et al, 15 Aly et al, 16 and Zhang et al 17 Phase I process control for profiles monitoring was discussed in Ding et al, 18 Kazemzadeh et al, 19 and Paynabar et al 20 Integration of the Phase I estimation of profile parameters with Phase II monitoring is discussed in Zou et al 21 Ren et al 22 proposed an EWMA‐like scheme with principal component analysis to monitor multichannel profiles. The goal of these profile control charts is to detect abrupt changes in profile parameters as fast as possible.…”
Section: Introductionmentioning
confidence: 99%