References of "Kazemzadeh, R. B"
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See detailOn the advantages of economically designed the Hotelling’s T2 control chart with variable sample sizes and sampling intervals
Faraz, Alireza ULg; kazemzadeh, R. B.; Parsian, Ahmad et al

in Quality & Quantity (2012), 46(1), 39-53

Faraz and Parsian (Statistical Paper, 47: 569–593, 2006) have shown that the double warning lines (DWL) scheme detects process shifts more quickly than the other variable ratio sampling schemes such as ... [more ▼]

Faraz and Parsian (Statistical Paper, 47: 569–593, 2006) have shown that the double warning lines (DWL) scheme detects process shifts more quickly than the other variable ratio sampling schemes such as variable sample sizes (VSS), variable sampling intervals (VSI) and variable sample sizes and sampling intervals (VSSVSI). In this paper, the DWLT2control chart for monitoring the process mean vector is economically designed. The cost model proposed by Costa and Rahim (Journal of Applied Statistics, 28: 875–885, 2001) is used here and is minimized through a genetic algorithm (GA) approach. Then the effects of the model parameters on the chart parameters and resulting operating loss is studied and finally a comparison between all possible variable ratio sampling (VRS) schemes are made to choose the best option economically. [less ▲]

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See detailEconomic and Economical Statistical Design of Hotelling’s T2 Control Chart with Two-State Adaptive Sample Size
Faraz, Alireza ULg; Saniga, Erwin; kazemzadeh, R. B.

in Journal of Statistical Computation & Simulation (2010), 80(12), 12991316

The Hotelling’s T 2 control chart, a direct analogue of the univariate Shewhart ¯X chart, is perhaps the most commonly used tool in industry for simultaneous monitoring of several quality characteristics ... [more ▼]

The Hotelling’s T 2 control chart, a direct analogue of the univariate Shewhart ¯X chart, is perhaps the most commonly used tool in industry for simultaneous monitoring of several quality characteristics. Recent studies have shown that using variable sampling size (VSS) schemes results in charts with more statistical power when detecting small to moderate shifts in the process mean vector. In this paper, we build a cost model of a VSS T 2 control chart for the economic and economic statistical design using the general model of Lorenzen and Vance [The economic design of control charts: A unified approach, Technometrics 28 (1986), pp. 3–11].We optimize this model using a genetic algorithm approach.We also study the effects of the costs and operating parameters on theVSS T 2 parameters, and show, through an example, the advantage of economic design over statistical design forVSS T 2 charts, and measure the economic advantage of VSS sampling versus fixed sample size sampling. [less ▲]

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See detailConstructing a fuzzy Shewhart control chart for variables when uncertainty and randomness are combined
Faraz, Alireza ULg; Kazemzadeh, R. B.; Moghadam, M. B. et al

in Quality & Quantity (2010), 44(5), 905-914

In this paper we introduce a fuzzy chart for variables which is used in situations when uncertainty and randomness are combined. It is showed that the Shewhart chart’s control limits must be adjusted in ... [more ▼]

In this paper we introduce a fuzzy chart for variables which is used in situations when uncertainty and randomness are combined. It is showed that the Shewhart chart’s control limits must be adjusted in these situations. However, this chart is based on a fuzzy acceptance region and this method arises when a decision should be made by referring to the grade of a sample statistic belonging to the fuzzy acceptance region. [less ▲]

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See detailThe Optimal Design of the VSI T2 Control Chart
Faraz, Alireza ULg; Kazemzadeh, R. B.; Heuchenne, Cédric ULg et al

in Journal of Iranian Statistical Society (2010), 9(1), 1-19

Recent studies have shown that the variable sampling interval (VSI) scheme helps practitioners detect process shifts more quickly than the classical scheme (FRS). In this paper, the economically and ... [more ▼]

Recent studies have shown that the variable sampling interval (VSI) scheme helps practitioners detect process shifts more quickly than the classical scheme (FRS). In this paper, the economically and statistically optimal design of the VSI T2 control chart for monitoring the process mean vector is investigated. The cost model proposed by Lorenzen and Vance (1986) is minimized through a genetic algorithm (GA) approach. Then the effects of the costs and operating parameters on the optimal design (OD) of the chart parameters and resulting operating loss through a fractional factorial design is systematically studied and finally, based on the ANOVA results, a Meta model to facilitate implementation in industry is proposed to determine the OD of the VSI T2 control chart parameters from the process and cost parameters [less ▲]

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