On the Monitoring of Linear Profiles in Multistage Processes

Ghahyazi, Masoumeh Eghbali; Niaki, Seyed Taghi Akhavan; Soleimani, Paria

doi:10.1002/qre.1531

Cited by 37 publications

(22 citation statements)

References 65 publications

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“…Phase-II monitoring of linear profiles in multistage processes has been investigated by authors including Esmaeeli and Sadeghieh (2013) and Eghbali Ghahyazi et al (2014). Soleimani et al (2009) studied the presence of within-profile autocorrelation in simple profile monitoring.…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

Phase-I monitoring of standard deviations in multistage linear profiles

et al. 2017

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In most modern manufacturing systems, products are often the output of some multistage processes. In these processes, the stages are dependent on each other, where the output quality of each stage depends also on the output quality of the previous stages. This property is called the cascade property. Although there are many studies in multistage process monitoring, there are fewer works on profile monitoring in multistage processes, especially on the variability monitoring of a multistage profile in Phase-I for which no research is found in the literature. In this paper, a new methodology is proposed to monitor the standard deviation involved in a simple linear profile designed in Phase I to monitor multistage processes with the cascade property. To this aim, an autoregressive correlation model between the stages is considered first. Then, the effect of the cascade property on the performances of three types of T 2 control charts in Phase I with shifts in standard deviation is investigated. As we show that this effect is significant, a U statistic is next used to remove the cascade effect, based on which the investigated control charts are modified. Simulation studies reveal good performances of the modified control charts.

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Section: Introduction and Literature Reviewmentioning

confidence: 99%

Phase-I monitoring of standard deviations in multistage linear profiles

et al. 2017

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“…Yang and Yeh (2011) proposed a cause-selecting control chart for the two-stage process with attribute data. Ghahyazi et al (2014) examined the effects of cascade property in multistage process in monitoring simple linear profile in Phase II. Davoodi et al (2015) monitored multistage Poisson count processes using exponentially weighted moving average (EWMA) and C control charts and proposed a changed point estimator to find the real time of a change in the process parameters.…”

Section: Introductionmentioning

confidence: 99%

Residuals based process capability indices for two-stage processes

2017

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The manufacturing operations often involve multistage processes where the process capability of each stage is affected by the process capability of its precedent processes. This property is known as the cascade property. The purpose of this paper is to estimate the process capability of the second stage of two-stage process while the cascade property impact is removed using residuals analysis. To this end, a method is proposed to determine the specification limits of the residuals based on the specification limits of the quality characteristics in the first and second stages. The C p , C pk and S pk indices are used to calculate the capability of the second stage in the two-stage process. The results of simulation study show the satisfactory performance of the proposed method in estimating the pure process capability of the second stage.

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“…Therefore, the probability of Type I error for each control chart is calculated by applying Eq. (13) such that the probability of Type I error equal to 0.0025 or, similarly, ARL 0 equal to 400 is obtained.…”

Section: Integrated Ewma (Da) and P-value (Da)mentioning

confidence: 99%

“…Ghahyazi et al [13] considered a two-stage process with simple linear pro le quality characteristic in each stage. They rst showed the e ect of cascade property on the statistical performance of T 2 control chart and then proposed a control chart based on the U statistic to monitor the process.…”

Section: Introductionmentioning

confidence: 99%

Monitoring multivariate-attribute quality characteristics in two stage processes using discriminant analysis based control charts

Zolfaghari

Amiri

2016

Scientia Iranica

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Abstract. In this paper, we focus speci cally on a two-stage process with multivariateattribute quality characteristics in the second stage. The main purpose of this study is extending Discriminant Analysis (DA) based control charts to monitor a two-stage process. We propose three methods including EWMA (DA), integrated EWMA (DA), and P-value (DA), and integrated Multivariate Exponentially Weighted Moving Average (MEWMA) and T 2 charts based on the DA approach to monitor the multivariate-attribute quality characteristic in a two-stage process. The performance of the proposed methods is evaluated through simulation studies as well as a real case.

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On the Monitoring of Linear Profiles in Multistage Processes

Cited by 37 publications

References 65 publications

Phase-I monitoring of standard deviations in multistage linear profiles

Phase-I monitoring of standard deviations in multistage linear profiles

Residuals based process capability indices for two-stage processes

Monitoring multivariate-attribute quality characteristics in two stage processes using discriminant analysis based control charts

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