The Application of Statistics as an Aid in Maintaining Quality of a Manufactured Product

Shewhart, W A

doi:10.1080/01621459.1925.10502930

Cited by 148 publications

(63 citation statements)

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“…In 1925, Shewhart published, "The Application of Statistics as an Aid in Maintaining Quality of a Manufactured Product." 8 In this, he explained how statistical methods help in estimating the significance of observed trends, thus assisting in the maintenance of the quality of the product. The theory of industrial quality improvement was further expanded by Juran and Deming who asserted that the key to quality improvement came in gathering and understanding data about the manufacturing process itself.…”

Section: Evolution Of Quality In Medicinementioning

confidence: 98%

Quality Assessment and Improvement in Colon and Rectal Surgery

Cook¹,

Hyman²

2004

Diseases of the Colon &Amp; Rectum

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Section: Evolution Of Quality In Medicinementioning

confidence: 98%

Quality Assessment and Improvement in Colon and Rectal Surgery

Cook¹,

Hyman²

2004

Diseases of the Colon &Amp; Rectum

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“…The vector i Y is a multivariate normal distribution When the process is in-control, Besides, and the q-dimensional observation with the mean vector, 0 μ , and covariance matrix, ∑ , the density function is given by (1) In any case the Mahalanobis distance of 1 μ from 0 μ is always unchanged and the shifted mean vector is 1 μ , the Mahalanob is distance is given by…”

Section: The Bayesian Modelmentioning

confidence: 99%

“…The basic idea of statistical process control originated in the American scholar Shewhart research for control charts, as in [1]. Then EWMA, CUSUM and Hotelling 2 T control chart were appeared.…”

Section: Introductionmentioning

confidence: 99%

Multivariate Bayesian VSI control chart

Zhang

Liu

Tan

2015

2015 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)

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In this paper, research was conducted on a multivariate Bayesian variable sampling interval (VSI) control chart to address the problem of insufficient research in the area of Bayesian multivariate control charts with variable parameters. Bayesian multivariate control chart was constructed and control strategies on variable sampling interval and variable control limits were designed. Cost model was built and the corresponding parameters of cost and control chart were determined through researching in enterprise. Monte Carlo stochastic simulation was adopted to verify the economical and statistical advantages of Bayesian multivariate control chart. This study provides supports for in-depth study on Bayesian multivariate control chart with variable parameters.

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“…The Average Run Length (ARL) is generally used to evaluate the performance of these charts. The first control schemes (Xbar-R, Xbar-S) emerged in 1925, and proposed by Shewhart (1925). Afterwards, EWMA (Roberts, 1959) and CUSUM (Page, 1954) charts were proposed, which are more sensitive to small variations.…”

Section: Introductionmentioning

confidence: 99%