The Experts below are selected from a list of 408042 Experts worldwide ranked by ideXlab platform
Peihsi Lee - One of the best experts on this subject based on the ideXlab platform.
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joint Statistical Design of x and s charts with combined double sampling and variable sampling interval
European Journal of Operational Research, 2013Co-Authors: Peihsi LeeAbstract:A combination of double sampling and variable sampling interval (DSVSI) charts can increase the efficiency of signaling small shifts. This study proposes joint DSVSI X¯ and s charts and investigates their Statistical performance. The proposed approach uses a Markov chain approach to compute the Statistical performance, and uses a Statistical Design model to Design DSVSI X¯ and s charts for detecting the mean shift and variance increase. A comparison study shows that the DSVSI X¯ and s charts are better able to signal the shifts of both mean and variance than joint double sampling X¯ and s chart, adaptive X¯ and R charts, EWMA, and CUSUM charts.
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an economic Statistical Design of double sampling control chart
International Journal of Production Economics, 2009Co-Authors: Chauchen Torng, Peihsi Lee, Naiyi LiaoAbstract:Abstract The double sampling (DS) X ¯ chart can reduce the sample size when monitoring the process mean. In this study, Duncan's cost model was modified by adding the Statistical constraints to develop the Design model of DS X ¯ chart for the optimization of Design parameters—sample size, control limit coefficient, warning limit coefficient and sampling interval. A numerical example was provided to illustrate the use of this model. A sensitivity analysis of the effects of model parameters and Statistical constraints on the optimal Design of DS X ¯ chart was also performed.
Arsen Grigoryan - One of the best experts on this subject based on the ideXlab platform.
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joint Statistical Design of double sampling x and s charts
European Journal of Operational Research, 2006Co-Authors: Arsen GrigoryanAbstract:Abstract In Statistical quality control, usually the mean and variance of a manufacturing process are monitored jointly by two Statistical control charts, e.g., a X ¯ chart and a R chart. Because of the efficiency of double sampling (DS) X ¯ charts in detecting shifts in process mean and DS s charts in process standard deviation it seems reasonable to investigate the joint DS X ¯ and s charts for Statistical quality control. In this paper, a joint DS X ¯ and s chart scheme is proposed. The Statistical Design of the joint DS X ¯ and s charts is defined and formulated as an optimization problem and solved using a genetic algorithm. The performance of the joint DS X ¯ and s charts is also investigated. The results of the investigation indicate that the joint DS X ¯ and s charts offer a better Statistical efficiency in terms of average run length (ARL) than combined EWMA and CUSUM schemes, omnibus EWMA scheme over certain shift ranges when all schemes are optimized to detect certain shifts. In comparison with the joint standard, two-stage samplings and variable sampling size X ¯ and R charts, the joint DS charts offer a better Statistical efficiency for all ranges of the shifts.
Naiyi Liao - One of the best experts on this subject based on the ideXlab platform.
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an economic Statistical Design of double sampling control chart
International Journal of Production Economics, 2009Co-Authors: Chauchen Torng, Peihsi Lee, Naiyi LiaoAbstract:Abstract The double sampling (DS) X ¯ chart can reduce the sample size when monitoring the process mean. In this study, Duncan's cost model was modified by adding the Statistical constraints to develop the Design model of DS X ¯ chart for the optimization of Design parameters—sample size, control limit coefficient, warning limit coefficient and sampling interval. A numerical example was provided to illustrate the use of this model. A sensitivity analysis of the effects of model parameters and Statistical constraints on the optimal Design of DS X ¯ chart was also performed.
Chauchen Torng - One of the best experts on this subject based on the ideXlab platform.
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an economic Statistical Design of double sampling control chart
International Journal of Production Economics, 2009Co-Authors: Chauchen Torng, Peihsi Lee, Naiyi LiaoAbstract:Abstract The double sampling (DS) X ¯ chart can reduce the sample size when monitoring the process mean. In this study, Duncan's cost model was modified by adding the Statistical constraints to develop the Design model of DS X ¯ chart for the optimization of Design parameters—sample size, control limit coefficient, warning limit coefficient and sampling interval. A numerical example was provided to illustrate the use of this model. A sensitivity analysis of the effects of model parameters and Statistical constraints on the optimal Design of DS X ¯ chart was also performed.
Ye Zhengfang - One of the best experts on this subject based on the ideXlab platform.
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application of an integrated Statistical Design for optimization of culture condition for ammonium removal by nitrosomonas europaea
PLOS ONE, 2013Co-Authors: Bao Yingling, Ye ZhengfangAbstract:Statistical methodology was applied to the optimization of the ammonium oxidation by Nitrosomonas europaea for biomass concentration (CB), nitrite yield (YN) and ammonium removal (RA). Initial screening by Plackett-Burman Design was performed to select major variables out of nineteen factors, among which NH4Cl concentration (CN), trace element solution (TES), agitation speed (AS), and fermentation time (T) were found to have significant effects. Path of steepest ascent and response surface methodology was applied to optimize the levels of the selected factors. Finally, multi-objective optimization was used to obtain optimal condition by compromise of the three desirable objectives through a combination of weighted coefficient method coupled with entropy measurement methodology. These models enabled us to identify the optimum operation conditions (CN = 84.1 mM; TES = 0.74 ml; AS = 100 rpm and T = 78 h), under which CB = 3.386×108 cells/ml; YN = 1.98 mg/mg and RA = 97.76% were simultaneously obtained. The optimized conditions were shown to be feasible through verification tests.