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See detailA modified economic-statistical design of the VP multivariate control charts
SEIF, Asghar; Faraz, Alireza ULg

Scientific conference (2012, January 15)

Hotelling’s T2 control chart is one of the most popular multivariate control charts for monitoring multiple variables simultaneously. Recent studies have shown that applying the T2 control chart by using ... [more ▼]

Hotelling’s T2 control chart is one of the most popular multivariate control charts for monitoring multiple variables simultaneously. Recent studies have shown that applying the T2 control chart by using a variable parameters (VP) scheme yields more rapid detection of assignable causes than the classical method of taking fixed sample sizes at fixed intervals of time. This paper presents an economic-statistical design (ESD) of the VP T2 control chart using the general model of Lorenzen and Vance. The genetic algorithm (GA) is then employed to search for the optimal values of the eight test parameters of the chart. Furthermore, VP and FRS schemes are compared with respect to the expect cost per unit time. [less ▲]

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See detailStatistical Merits and Economic Evaluation of T2 Control Charts with the VSSC Scheme
Seif, Asghar; Moghadam, M.B.; Faraz, Alireza ULg et al

in Arabian Journal for Science and Engineering (2011), 36(7), 1461-1470

T2 control charts are used to monitor a process when more than one quality variable associated with the process is being observed. Recent studies have shown that using variable sampling size (VSS) schemes ... [more ▼]

T2 control charts are used to monitor a process when more than one quality variable associated with the process is being observed. Recent studies have shown that using variable sampling size (VSS) schemes results in charts with more statistical power for detecting small to moderate shifts in the process mean vector. This paper presents an economic-statistical design of T2 control charts with variable sample size and control limits (VSSC). We build a cost model of a VSSC T2 control chart for the purpose of economic-statistical design using the model of Costa and Rahim (J. Appl. Stat. 28:875–885, 2001). This cost model constructed involves the cost of false alarms, the cost of finding and eliminating an assignable cause, the cost associated with production in an out-of-control state, and the cost of sampling and testing. We optimize this model using a genetic algorithm approach. Furthermore, VSSC and VSS T2 charts are compared with respect to the expected cost per unit time. [less ▲]

Detailed reference viewed: 59 (24 ULg)