Statistical Process Control for Real-World Applications

Levinson, William A.

doi:10.1201/b10467

Cited by 15 publications

(7 citation statements)

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“…Detailed analysis of the dynamics of traffic accidents with the usage of control charts have been conducted in case of two developing countries: Poland, a transit country between the Eastern Europe and the West, which is the member of the European Union; Ukraine, in which the road law is considered a significantly liberal and in contrast one of the Scandinavian countries, Sweden, considered to be highly developed, where the culture of driving and the quality of roads is at a high level, and the penalties for driving offenses are a deterrent high. In this case data derived from the Economic Commission for Europe (ECE) 5 had been used. Individual data had been compared with the average results for Europe.…”

Section: The Results Of the Analysismentioning

confidence: 99%

The Study of the Dynamics of Traffic Accidents Using the Control Charts

Rębisz¹

2013

MMR

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The aim of this article is an attempt to use the control chart for the average to study the dynamics of traffic accidents in selected European countries. The study covered the three countries: Poland, Ukraine and Sweden for the period 1993-2008. The obtained results were compiled with the European average-annual number of accidents for 42 countries. The analysis confirmed that according to common opinion Sweden has the lowest average of accidents, while Ukraine oscillates around the European canon, which may be surprising, considering the fact that Ukraine is seen by many as a country with low and high culture of driving accidents. The analysis showed that the worst ranks shows Poland, which differs significantly from the European average in spite of the positive trend noticeable since 1997. It was also found that the liberalization of rules and increase the number of cars contributed negatively to the increase in the number of accidents (Ukraine), and exacerbation of traffic regulations had a positive impact on test feature (Poland). It should be emphasized that the website of the European Economic Commission, which the data were collected from has no information for subsequent periods. It is therefore difficult to determine whether the positive trend of Poland development remains at a similar level, and within the next four years, i.e. until 2012 it managed to get closer to the expected level in Europe. In the case of Ukraine the opposite trend can be observed, but again for the same reasons it is hard to determine whether the negative trend was prevented. It is also not possible to examine what impact on the development of the number of accidents in Poland and Ukraine had the organization of mass events such as Euro2012 and related with it multimillion-dollar expenditure on the improvement of road infrastructure.

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Section: The Results Of the Analysismentioning

confidence: 99%

The Study of the Dynamics of Traffic Accidents Using the Control Charts

Rębisz¹

2013

MMR

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“…Individual-moving range charts are recommended in industry when single measurements are collected at a given time (Levinson 2010 ) as it happens with the monitoring of bipolar disorder patients. They are a pair of charts in which the first one displays the individual observations, with control limits based on their average and standard deviation estimated using the average moving range of pairs of consecutive measurements.…”

Section: Methodsmentioning

confidence: 99%

Control charts for monitoring mood stability as a predictor of severe episodes in patients with bipolar disorder

Vazquez-Montes

Stevens

Perera

et al. 2018

Int J Bipolar Disord

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BackgroundRecurrent mood episodes and subsyndromal mood instability cause substantial disability in patients with bipolar disorder. Early identification of mood episodes enabling timely mood stabilization is an important clinical goal. This study investigates the ability of control chart methodology to predict manic and/or depressive episodes by applying Shewhart’s control rules to weekly self-reported scores from mania and depression questionnaires.MethodsShewhart’s control rules were applied to weekly self-reported scores from the Altman Self-Rating Mania Scale (ASRM) and the Quick Inventory of Depressive Symptomatology—Self-Report (QIDS) collected from 2001 to 2012 as part of the OXTEXT programme. Manic and depressive episodes were defined as an ASRM score ≥ 10 or a QIDS score ≥ 15, respectively. An episode-free run-in period of eight consecutive weeks without an episode of either type was used to calibrate control charts. Shewhart’s rules were then applied to follow-up data. Their sensitivity and positive predictive value for predicting manic or depressive episodes within the next 4 weeks were calculated focusing on the first episode. Secondary analyses varying control chart type, length of episode-free run-in period, time frames to evaluate diagnostic accuracy, thresholds defining either manic or depressive episodes, and missing data methods were performed.ResultsData from 146 participants (37% men) were included. The mean age was 43.4 (SD = 13.3) years. The median follow-up was 10 (IQR 5–40) weeks for mania and 10 (IQR 5–23) weeks for depression. A total of 53 (36%) participants had a manic episode and 67 (46%) had a depressive episode. For manic episodes, the sensitivity and positive predictive value of Shewhart’s control rules were 30% (95% CI 19–45%) and 7% (95% CI 5–9%), and for depressive episodes, 33% (95% CI 22–46%) and 9% (95% CI 6–12%), respectively. Results from secondary analyses were similar to these.ConclusionsTele-monitoring with control rules has the potential to predict about one-third of manic or depressive episodes before they occur, at the cost of a high false positive rate. Given the severe consequences of manic and depressive episodes, this trade-off may be desirable.Electronic supplementary materialThe online version of this article (10.1186/s40345-017-0116-2) contains supplementary material, which is available to authorized users.

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“…En la carta de control para |S| se usa la media y la varianza de |S| como E(|S|) y V(|S|) y se tiene en cuenta la propiedad que indica que el intervalo E|S|±3√(V(|S|)) contiene la mayor parte de la distribución de |S| (Montgomery, 2009). De acuerdo con Levinson (2011), se puede demostrar que el determinante esperado y la línea central de la carta es 4y la varianza del determinante está dada como,…”

Section: Metodologíaunclassified

Propuesta de Carta de Control Multivariada utilizando la Media Winsorizada basada en la Carta |S| / Proposed Multivariate Control Chart using Winsorized Mean based on the |S| Chart

2018

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Resumen— El monitoreo global de la calidad de un producto está sujeto a la evaluación simultánea de varias de sus características; es necesario bajo estas condiciones la implementación de las cartas de control tipo multivariadas. La variabilidad, en este caso la matriz de varianza covarianza, es sin duda el más importante de los estadísticos desde la perspectiva multivariada, que puede ser monitoreada con distintas cartas. Entre éstas se encuentran: las cartas Shewhart, CUSUM y EWMA. En este artículo se desarrolla una metodología de implementación de la Media Winsorizada en la carta de control multivariada de varianza efectiva |S|, encontrando una gran utilidad en procesos con valores extremos. El estudio muestra además una comparación entre la carta de control tradicional multivariante y la carta propuesta, que muestra mayor sensibilidad.Abstract— The global quality monitoring of a product is often subject to the simultaneous evaluation of several of its features; under these circumstances it is necessary to implement multivariate control charts. Variability, in this particular case, the variance-covariance matrix is indisputably the most important of the statistics from the multivariate perspective and it can be monitored with different charts, among these: Shewhart, CUSUM and EWMA. This article develops the Winsorized Mean in the effective variance multivariate control |S|-chart implementation methodology and it was demonstrated that the modification was more efficient when the sample hat outliers. This study shows a comparison between the traditional multivariate control chart and a proposed chart which was found to have more sensitivity.

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Statistical Process Control for Real-World Applications

Cited by 15 publications

References 0 publications

The Study of the Dynamics of Traffic Accidents Using the Control Charts

The Study of the Dynamics of Traffic Accidents Using the Control Charts

Control charts for monitoring mood stability as a predictor of severe episodes in patients with bipolar disorder

Propuesta de Carta de Control Multivariada utilizando la Media Winsorizada basada en la Carta |S| / Proposed Multivariate Control Chart using Winsorized Mean based on the |S| Chart

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