Multi-objective economic-statistical design of MEWMA control chart

Amiri, Amirhossein; Mogouie, Hamed; Doroudyan, Mohammad Hadi

doi:10.1504/ijpqm.2013.052021

Cited by 11 publications

(3 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This model can be used by terminal managers of Valencia Port to implement better control techniques, and thus it improves the quality of service. Amiri et al (2013) used two multi-objective approaches and compared a multivariate exponentially weighted moving average (MEWMA) control chart for an economic-statistical design. They showed that their proposed method could have an economic-statistical model of MEWMA control charts and use of non-integrative approach, and decision makers and managers can find various solutions.…”

Section: Introductionmentioning

confidence: 99%

On bivariate control charts for the mean of autocorrelated process

Gorgin

Gildeh

Sarmad

et al. 2021

IJPQM

View full text Add to dashboard Cite

The major problem in analysing control charts is to work with autocorrelated data. This problem can be solved by fitting a suitable model to data and using the control chart for the residuals. In most papers, the average run length (ARL) criterion has been used to evaluate the effect of autocorrelation on the performance of control chart. But, in this paper, we compare the efficiency of standardised and modified control charts with residuals charts in identifying changes in the mean process in the presence of autocorrelation using the false positive rate and the false negative rate criteria, and also the comparison between the results of this criterion and the results of ARL criterion is discussed.

show abstract

Section: Introductionmentioning

confidence: 99%

On bivariate control charts for the mean of autocorrelated process

Gorgin

Gildeh

Sarmad

et al. 2021

IJPQM

View full text Add to dashboard Cite

show abstract

“…MEWMA control procedure had been research with DD-Diagram performance to compare through a real example on individual observations taken from a multivariate quality process also discussed by Hajlaoui [13]. The high costs of implementing MEWMA control chart, the economic statistical design of this chart has been increasingly investigated had been explained with Amiri et al [14]. Hamed [15] and Knoth [16] find the ARL numeric for MEWMA charts.…”

Section: Introductionmentioning

confidence: 99%

The Use Of MEWMA Control Chart In Controlling Major Component Of Cement Product

Sari¹,

Devianto²

2020

Proceedings of the Proceedings of the 1st International Conference on Statistics and Analytics, ICSA 2019, 2-3 August 2019, Bog

View full text Add to dashboard Cite

Cement is one of the industrial products that has a quality control process. Major component that consists of SiO 2 , Al 2 O 3 , Fe 2 O 3 , CaO, MgO and SO 3 as basic component in cement product. This research explains about quality control of major component of cement by using MEWMAcontrol chart.The way to measure the performance of the control chart is used ARL as the average run observation to find the first out of control data. ParameterARL 0 is the average run observation of in control data. In this research, it is assumed the data was in control. The optimization of ARL 0 by weighted parameter of MEWMA control chart for λ=1, that is equal to Hotteling T 2 chart. Optimal value of the weight parameter is determined by using the bisection method for then the variables did not show the outlier data. Finally, this research shows that cement production process is in control.

show abstract

“…Khoo et al (2013) and Tu (2013) have developed economic and economic-statistical designs for two unit series system x chart and synthetic x chart. Amiri et al (2013) provided economic statistical design of modified exponentially weighted moving average (MEWMA) control chart. Franco et al (2014) have investigated economic-statistical design of x charts using skip sampling strategies for autocorrelated processes.…”

Section: Introductionmentioning

confidence: 99%

Economic design of moving average control chart for non-normally distributed data: a comparative study

Patil¹,

Shirke

2017

IJOR

View full text Add to dashboard Cite

An economic cost function for moving average control chart under non-normal quality characteristic is obtained using continuous and ceased production modes. This cost function can be used to obtain optimal design parameters which minimise the loss cost per hour of the production. Burr distribution has been used to transform the non-normal data to normal. Sensitivity analysis of the economic design is also discussed. The ceased process is observed to be dominant with significant saving in the cost over the continuous process.

show abstract

Multi-objective economic-statistical design of MEWMA control chart

Cited by 11 publications

References 42 publications

On bivariate control charts for the mean of autocorrelated process

On bivariate control charts for the mean of autocorrelated process

The Use Of MEWMA Control Chart In Controlling Major Component Of Cement Product

Economic design of moving average control chart for non-normally distributed data: a comparative study

Contact Info

Product

Resources

About