Designing of a new monitoring t-chart using repetitive sampling

Aslam, Muhammad; Khan, Nasrullah; Azam, Muhammad; Jun, Chi‐Hyuck

doi:10.1016/j.ins.2014.01.022

Cited by 79 publications

(39 citation statements)

References 24 publications

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“…Abbas et al proposed an improved S 2 chart based on the modified successive sampling scheme. Aslam et al proposed a t ‐chart based on the repetitive sampling scheme. Both of these studies showed a better performance of their proposed structures compared with the charts based on the usual simple random sampling scheme.…”

Section: Introductionmentioning

confidence: 99%

Location charts based on ranked set sampling for normal and non‐normal processes

Abbasi

2019

Quality & Reliability Eng

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Control charts, based on ranked set sampling schemes, had been proposed recently for efficient monitoring of process location. All the proposals in the literature are based on the ideal assumption of normally distributed quality characteristics. No study as of yet investigated the performance of location charts based on ranked set sampling for non-normal processes. In this study, we investigated the location Y chart based on simple random sampling (SRS) and three well-known rank-based schemes ie, ranked set sampling (RSS), median ranked set sampling (MRSS), and extreme ranked set sampling (ERSS), considering normal and a variety of non-normal parent distributions. Both heavy-tailed symmetric and skewed cases have been considered in this study. The performance of the charts is evaluated using average run length (ARL), extra quadratic loss (EQL), and relative ARL (RARL) measures. A real life example is also presented that details the monitoring of pH levels in water for an experiment conducted to study the reproduction of Mysids. The study will help quality practitioners to choose the Y chart based on an efficient sampling scheme for normal and non-normal processes. KEYWORDS average run length, extra quadratic loss, location parameter, non-normality, pH level, ranked set sampling Qual Reliab Engng Int. 2019;35:1603-1620.wileyonlinelibrary.com/journal/qre

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Section: Introductionmentioning

confidence: 99%

Location charts based on ranked set sampling for normal and non‐normal processes

Abbasi

2019

Quality & Reliability Eng

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“…These censoring schemes have been widely used in the area of life‐testing sampling plan, see, for example, other studies . More details about control charts can be seen in other works …”

Section: Introductionmentioning

confidence: 99%

“…[18][19][20][21][22] More details about control charts can be seen in other works. [23][24][25] The Weibull distribution is very popular for life test experiment because of its flexibility of using two parameters. The Weibull distribution has been used in variety of fields, see, for example, Montgomery et al [26][27][28][29] designed a control chart for the Weibull distribution.…”

Section: Introductionmentioning

confidence: 99%

A new variable control chart under failure‐censored reliability tests for Weibull distribution

Khan

Aslam

Raza

2018

Quality & Reliability Eng

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In this paper, we propose a new variable control chart under type II or failure‐censored reliability tests by assuming that the lifetime of a part follows the Weibull distribution with fixed and stable shape parameter. The purpose is to monitor the mean and the variance of a Weibull process. In fact, the mean and the variance are related to the scale parameter. The necessary measures are given to calculate the average run length (ARL) for in‐control and shifted processes. The tables of ARLs are presented for various shift constants and specified parameters. A simulation study is given to show the performance of the proposed control chart. The efficiency of the proposed control chart is compared with a control chart based on the conditional expected value under type II censoring. An example is also given for the illustration purpose.

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“…However, in the repetitive sampling, the process is repeated until a decision is made on the basis of the current sample if the experimenter cannot reach a decision from the previous samples (Sherman, 1965;Balamurali and Jun, 2006). Ahmad et al (2013) and Aslam et al (2014) introduced the repetitive sampling in the area of control charts.…”

Section: Introductionmentioning

confidence: 99%

New Attributes and Variables Control Charts under Repetitive Sampling

Aslam¹,

Azam²

2014

Industrial Engineering and Management Systems

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New control charts under repetitive sampling are proposed, which can be used for variables and attributes quality characteristics. The proposed control charts have inner and outer control limits so that repetitive sampling may be needed if the plotted statistic falls between the two limits. Particularly, the new np and variable X-bar control charts under repetitive sampling are considered in detail. The in-control and out-of-control average run lengths are analyzed according to various process shifts. The performance of the proposed control charts is compared with the existing np and the X-bar control charts in terms of the average run lengths.

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Designing of a new monitoring t-chart using repetitive sampling

Cited by 79 publications

References 24 publications

Location charts based on ranked set sampling for normal and non‐normal processes

Location charts based on ranked set sampling for normal and non‐normal processes

A new variable control chart under failure‐censored reliability tests for Weibull distribution

New Attributes and Variables Control Charts under Repetitive Sampling

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