Poisson EWMA Control Charts

Borror, Connie M.; Champ, Charles W.; Rigdon, Steven E.

doi:10.1080/00224065.1998.11979871

Cited by 158 publications

(125 citation statements)

References 9 publications

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“…If the observations are from ZINB model, the expected value and variance of ZINB could be obtained from (6) approaches one as i gets larger. The control limits of ZINB EWMA control chart can be shown as…”

Section: Zero-inflated Negative Binomial Modelmentioning

confidence: 99%

“…Gan [5] proposed a CUSUM chart for binomial counts based on the CUSUM statistics. Borror et al [6] proposed the EWMA control chart for monitoring Poisson data. Khoo [7] proposed the moving average control chart for monitoring the fraction non-conforming.…”

Section: Introductionmentioning

confidence: 99%

“…Then, the out-of-control ARL (ARL 1 ) should be small for out-of-control situation. Many methods for evaluating the ARL for control charts have been studied in many literatures [4]- [6]. A simple method as Monte Carlo simulation is often used to verity and accuracy.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The ARL of EWMA Chart for Monitoring ZINB Model Using Markov Chain Approach

Chananet¹,

Sukparungsee²,

Areepong³

2014

IJAPM

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Abstract-In this paper, we proposed the Markov Chain Approach (MCA) to evaluate the average run length (ARL) of exponentially weighted moving average (EWMA) control chart when zero-inflated counted are observed in a negative binomial model. Furthermore, the efficiency of the MCA is compared with Monte Carlo Simulation via the CPU times which the former is much saving computational times used when compared with the latter method.Index Terms-Exponentially weighted moving average, zero-inflated negative binomial, average run length, markov chain, computational times.

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Section: Zero-inflated Negative Binomial Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The ARL of EWMA Chart for Monitoring ZINB Model Using Markov Chain Approach

Chananet¹,

Sukparungsee²,

Areepong³

2014

IJAPM

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“…Gan [11] introduced three modified EWMA charts for Poisson data. Borror et al [12] proposed a better procedure for using the EWMA chart for a Poisson count. Somerville et al [13] developed a smoothing and filtering method using the EWMA and Poisson probabilities, which separates the two distributions in a particle count data stream into a base process and an outlier process followed by applying statistical monitoring schemes to each of them.…”

Section: Literature Reviewmentioning

confidence: 99%

A Heuristic Fixed Limit Bayesian P Chart

Abooie

Nayeri

2009

The South African Journal of Industrial Engineering

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The paper proposes an efficient approach to detecting an increase in the fraction of nonconforming items. The novelty of the paper is its utilization of the concept of the Bayesian rule and construction of a Bayesian control chart. This approach is significantly better than certain existing effective approaches in detecting small deviations. The major application of the charts is in high-tech industries and short run processes where the detection of small deviations and the evaluation of the initial setup are very important. The simulated results for the average run length profiles demonstrate the superiority of the new approach against the standard p chart, binomial EWMA and moving average approach. The new approach is easy to understand and may be attractive and useful to researchers, while it can also be an effective alternative for other existing approaches. OPSOMMINGDie navorsing hou 'n doeltreffende Bayes-gebaseerde kontrolekaartmetode voor vir die beheer van breukdefekte waar gehalte buite beheer raak vir klein afwykings. Die metode se vertoning word via simulasie teen ander geykte kontrolekaartmetodes vir gemiddelde looplengte beproef. Die nuwe benadering is maklik verstaanbaar en bruikbaar vir navorsers, terwyl dit ook 'n effektiewe alternatief vir ander bestaande benaderings is.118

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“…Gan (1990) proposed three modified EWMA charts for the Poisson data. A better procedure for using the EWMA chart for Poisson count is given by Borror, Champ & Rigdon (1998). Somerville, Montgomery & Runger (2002) developed a smoothing and filtering method using the EWMA and Poisson probabilities which separates the two distributions in a particle count data stream into a base process and an outlier process followed by applying statistical monitoring schemes to each of them.…”

Section: Introductionmentioning

confidence: 99%