Performance of Shewhart Chart and Multivariate Hotelling T-Square Control Chart in Textile Industry

S. Subbulakshmi; A. Kachimohideen; R. Sasikumar

doi:10.29055/jcms/920

Double sampling control chart for a first order autoregressive process

Pesquisa Operacional ◽

10.1590/s0101-74382008000300008 ◽

2008 ◽

Vol 28 (3) ◽

pp. 545-562 ◽

Cited By ~ 8

Author(s):

Fernando A. E. Claro ◽

Antonio F. B. Costa ◽

Marcela A. G. Machado

Keyword(s):

Sample Size ◽

Closed Form ◽

Control Chart ◽

Autoregressive Model ◽

Average Run Length ◽

Autoregressive Process ◽

Double Sampling ◽

First Order ◽

Shewhart Chart ◽

Sampling Intervals

In this paper we propose the Double Sampling control chart for monitoring processes in which the observations follow a first order autoregressive model. We consider sampling intervals that are sufficiently long to meet the rational subgroup concept. The Double Sampling chart is substantially more efficient than the Shewhart chart and the Variable Sample Size chart. To study the properties of these charts we derived closed-form expressions for the average run length (ARL) taking into account the within-subgroup correlation. Numerical results show that this correlation has a significant impact on the chart properties.

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KOMPUTASI METODE MULTIVARIATE EXPONENTIALLY WEIGHTED MOVING AVERAGE (MEWMA) UNTUK PENGENDALIAN KUALITAS PROSES PRODUKSI MENGGUNAKAN GUI MATLAB (STUDI KASUS: PT. Pismatex Textile Industry Pekalongan)

Jurnal Gaussian ◽

10.14710/j.gauss.v9i3.28908 ◽

2020 ◽

Vol 9 (3) ◽

pp. 283-291

Author(s):

Riza Fahlevi ◽

Hasbi Yasin ◽

Dwi Ispriyanti

Keyword(s):

Control Chart ◽

Textile Industry ◽

Control Charts ◽

Moving Average ◽

Exponentially Weighted Moving Average ◽

Quality Control Tool ◽

Weight Value ◽

Mewma Control Chart ◽

Weighted Moving Average ◽

Exponentially Weighted

Control chart is one of the effective statistical tools to overcome the problem of process quality in a production. Multivariate Exponentially Weighted Moving Average (MEWMA) control chart is an effective quality control tool in processes with more than one variable and correlated (multivariate). The MEWMA control chart has a weight value (λ) which makes this chart more sensitive in detecting small shifts process mean. The weight (λ) has values ranging from 0 to 1 ( ), where this weight will be given to each data. The MEWMA control chart in this study was used to form a control chart by the product defects percentage of grade B and grade B at PT. Pismatex Textile Industry Pekalongan. In this study, GUI Matlab was formed to assist the computational process in forming MEWMA control charts to control the quality of production at PT. Pismatex Textile Industry Pekalongan. Based on the result, the optimal weight is obtained at the weight value λ = 0.9. Keywords: Multivariate Exponentially Weighted Moving Average (MEWMA), Weight (λ), GUI Matlab, Percentage of product defects.

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A Comparative Analysis of Control Charts for Monitoring Process Mean

Turkish Journal of Computer and Mathematics Education (TURCOMAT) ◽

10.17762/turcomat.v12i3.1263 ◽

2021 ◽

Vol 12 (3) ◽

pp. 2616-2622

Author(s):

You Huay Woon

Keyword(s):

Control Chart ◽

Control Charts ◽

Moving Average ◽

False Alarms ◽

Synthetic Control ◽

Implementation Cost ◽

Shewhart Chart ◽

Monitoring Process ◽

Synthetic Chart ◽

The Cost

Control charts serve as an effective tool for controlling and monitoring process quality in industries of production and service. The Shewhart chart is the first control chart that was used to detect large mean shifts in a process. Since then, to increase the Shewhart chart’s sensitivity, synthetic type control charts, such as synthetic control chart, side sensitive group runs (SSGR) control chart, have been proposed. SSGR chart ismore efficient compared to the Shewhart chart and synthetic chart,primarily due to the side sensitive feature in SSGR chart. Meanwhile, exponentially weighted moving average (EWMA) chart isoften used to detect small process changes. In practice, the evaluation of a control chart’s performance is vital. Nevertheless, the cost of implementing a control chart is an important factor that influences the choice of a control chart. The cost of repairs, sampling, nonconforming products from a failure in detecting out-of-control status, and investigating false alarms, can be significantly high. Therefore, the aim of this paper is to compare the implementation cost of synthetic, SSGR and EWMA charts, so that quality practitioners can identify the most cost-effective chart to implement. Here, the cost function was adopted to compute the implementation cost of the control chart. According to the findings, quality practitioners are recommended to adopt the SSGR chart,since it is more economical compared to the synthetic chart. However, the cost to implement anEWMA chart is higher than the synthetic and SSGR charts. In light of this, this study allows for quality practitioners to have a better idea on the selection of the control chart to implement, with respect to its cost.

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Common Statistic Technology Applied to the Product Quality Control

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.670-671.1588 ◽

2014 ◽

Vol 670-671 ◽

pp. 1588-1592

Author(s):

Xiao Qing Wang ◽

Bing Liu ◽

Yong Gui Liu

Keyword(s):

Quality Control ◽

Control Chart ◽

Textile Industry ◽

Statistical Control ◽

Pareto Chart ◽

Process Capability Analysis ◽

Correlation And Regression Analysis ◽

Line Chart ◽

Capability Analysis ◽

Operation Procedure

This paper studies the convenient application of statistical control methods in quality control, which includes selecting Pareto chart, line chart, process capability analysis, correlation and regression analysis, orthogonal test and the control chart. The purpose, range and operation steps of these methods are in practical use in the textile industry. Furthermore, this paper describes the application of control chart by using standard operation procedure.

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Novel Stage Decorations-A New Branch of Textile Industry

Scientific American ◽

10.1038/scientificamerican11051910-358a ◽

1910 ◽

Vol 103 (19) ◽

pp. 358-358

Author(s):

Arthur H. J. Keane

Keyword(s):

Textile Industry

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Collective Resource Mobilisation for Economic Survival within the Kurdish and Turkish Communities in London

BORDER CROSSING ◽

10.33182/bc.v6i2.492 ◽

2016 ◽

Vol 6 (2) ◽

pp. 219-239

Author(s):

Olgu Karan

Keyword(s):

Small Business ◽

Textile Industry ◽

Economic Capital ◽

Small Business Owners ◽

Coffee Shop ◽

Business Ownership ◽

Economic Survival ◽

Collective Resource ◽

Resource Mobilisation ◽

Depth Interviews

This paper proposes a new conceptual framework in understanding the dynamics within the Kurdish and Turkish (KT) owned firms in London by utilising Charles Tilly’s work concerning collective resource mobilisation. Drawing on 60 in-depth interviews with restaurant, off-licence, kebab-shop, coffee-shop, supermarket, wholesaler owners and various community organisations, the paper sheds light upon the questions of why and how the KT communities in London moved into, and are over represented and why Turkish Cypriots are absent in small business ownership. The re-search illustrates that members of the KT communities aligned in their interests to become small business owners after the demise of textile industry in the midst of 1990s in London. The interest alignment in small business ownership required activation of various forms of capital and transposition of social, cultural and economic capital into one another.

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