Economic statistical design of non-uniform sampling scheme X bar control charts under non-normality and Gamma shock using genetic algorithm

Chen, F. L.; Yeh, C. H.

doi:10.1016/j.eswa.2009.01.018

Cited by 39 publications

(15 citation statements)

References 40 publications

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“…Then optimal parameters are those with values that minimize the expected cost per hour defined by the cost model [1,2]. The first cost model for the economic design of X-bar control charts was proposed by Duncan in 1956 and considered exponential failure distribution [3].…”

Section: Introductionmentioning

confidence: 99%

“…The first cost model for the economic design of X-bar control charts was proposed by Duncan in 1956 and considered exponential failure distribution [3]. Since then many other works have proposed cost models with different characteristics and conditions (i.e., Weibull and Gamma failure distributions [1,4,5], variable sampling intervals [6 -8], integration with other charts as R and S for variability [9]). …”

Section: Introductionmentioning

confidence: 99%

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Analyzing the effect of non-normality on the solution space for the economic statistical design of X-bar control charts

Caballero‐Morales

Rahim

2015

2015 International Conference on Industrial Engineering and Operations Management (IEOM)

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the assumption of normality is commonly considered when designing X-bar control charts. However in practice sometimes the measurements of the quality attribute are not normally distributed, especially when the size of the sample is small. For the economic statistical design of X-bar control charts the assumption of non-normality is important as it has significant effect on the estimation of the chart's parameters (n,h,k). In this paper the effect of non-normality on the solution space for the economic statistical design of X-bar control charts is studied. Considering constant sampling intervals it was observed that the assumption of non-normality reduces the valid range of k. In contrast for variable sampling intervals it was observed that the non-normal assumption has a significant effect on the lower bound for h. By understanding how the solution space is restricted by the non-normality assumption more effective solving algorithms for this problem can be developed.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Analyzing the effect of non-normality on the solution space for the economic statistical design of X-bar control charts

Caballero‐Morales

Rahim

2015

2015 International Conference on Industrial Engineering and Operations Management (IEOM)

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“…Karr and Gentry [12] showed that GA is different from other optimization tools based on the following reasons: it considers many points in a search space simultaneously; GA works directly with set of parameters characterized as strings of chromosomes instead of parameters themselves; and in the guide, its search applies probabilistic rules not deterministic rules. It has been applied to many economic and economic-statistical designs of control charts for example, see Chou et al [13], Chen and Yeh [14], Kaya [15], and Niaki et al [16].…”

Section: Introductionmentioning

confidence: 99%

Robust economic and economic-statistical design of EWMA control chart

Amiri

Moslemi

Doroudyan

2014

Int J Adv Manuf Technol

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Uncertainty in the cost and process parameters is very common in practice. In this paper, we develop a scenariobased robust economic and economic-statistical design of exponentially weighted moving average control chart to account for economic and statistical criteria as well as the uncertainty. For this purpose, we use Lorenzen and Vance cost function for economic and economic-statistical design of an exponentially weighted moving average control chart in the real applications. Absolute robustness criterion which minimizes the worst-case scenario and also robust deviation which minimizes the deviation from the optimal solutions are applied to explore the robust approach for robust design of the exponentially weighted moving average control chart. The optimization models are solved by using the genetic algorithm. The performance of the proposed methods is illustrated through two numerical examples. Finally, the application of the proposed methods is illustrated in a real manufacturing case in the tile production industry.

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“…Vommi and Murty [8] presented an economic design of X chart in which the input parameters are expressed as ranges. Some of researchers studied the economic design of X control chart for monitoring a process under non-normality (see, e.g., [14] and [15]). …”

Section: Introductionmentioning

confidence: 99%

Multi-objective economic statistical design of X-bar control chart considering Taguchi loss function

Safaei

Kazemzadeh

Niaki

2011

Int J Adv Manuf Technol

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Shewhart charts are the most popular control charts that can be used to monitor variable quality characteristics in a production process. In this paper, a multi-objective model of the economic statistical design of the X-bar control chart is first proposed by incorporating the Taguchi loss function and the intangible external costs. The model minimizes the mean hourly loss cost while minimizing out-of-control average run length and maintaining reasonable in-control average run length. A multiobjective evolutionary algorithm, namely NSGA-II, is then developed and used to obtain the Pareto optimal solution of the model. Some sensitivity analyses are next performed to investigate the effect of parameter estimation on the chart performances. Finally, a comparison study with a traditional economic design model reveals that the proposed multiple objective design of the X-bar control chart offers a better approach and more practical outcomes for the practitioners.

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Economic statistical design of non-uniform sampling scheme X bar control charts under non-normality and Gamma shock using genetic algorithm

Cited by 39 publications

References 40 publications

Analyzing the effect of non-normality on the solution space for the economic statistical design of X-bar control charts

Analyzing the effect of non-normality on the solution space for the economic statistical design of X-bar control charts

Robust economic and economic-statistical design of EWMA control chart

Multi-objective economic statistical design of X-bar control chart considering Taguchi loss function

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