Projeto econômico de cartas adaptativas para monitoramento de processos

Michel, Renato; Fogliatto, Flávio Sanson

doi:10.1590/s0104-530x2002000100003

Cited by 9 publications

(4 citation statements)

References 17 publications

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“…Após esta análise deve-se atuar sobre estas causas com fins de melhoria contínua. (MICHEL & FOGLIATTO, 2002). Segundo o Portal Action primeiro, para elaborar uma carta de controle determina-se primeiro o que será controlado, o tipo gráfico a ser selecionado depende da característica da qualidade a ser controlada.…”

Section: Cartas De Controleunclassified

Gestão pela qualidade - volume 2

Andrade¹

2018

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Section: Cartas De Controleunclassified

Gestão pela qualidade - volume 2

Andrade¹

2018

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“…The SPC is one of the classical statistical quality control techniques and it assumes that there is a process-inherent variation called natural variation, which is usually caused by many variables that individually produce small effects and are difficult to be detected and eliminated. On the other hand, there are special causes that produce great effects, and they are fewer and easier to be detected (Woodall, 2000;Michel & Fogliatto, 2002;Montgomery & Runger, 2003). The distinction between common and special cause is context-dependent -a common cause today may be a common cause tomorrow -and it could affect the sampling process (Woodall, 2000).…”

Section: Theoretical Foundation 21 Basic Concepts Of Spcmentioning

confidence: 99%

Método de estimativa dos limites da carta de controle não paramétrica que monitora simultaneamente a média e variância

et al. 2015

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Resumo Os gráficos de controle clássicos para variáveis contínuas monitoram, separadamente, as medidas de posição central e de dispersão, conhecidas também como medidas de locação e escala. O monitoramento desses parâmetros tem como pressuposto que a distribuição de probabilidade dos dados seja conhecida e siga o padrão normal, o que, em situações práticas, nem sempre ocorre. Para isso foram desenvolvidos os chamados gráficos de controle não paramétricos. Este trabalho tem como objetivo desenvolver um método para determinar os limites de controle estatístico de gráficos de controle com distribuição de probabilidade desconhecida e que monitore simultaneamente as medidas de locação e escala. O método de pesquisa utilizado integra técnicas de experimentos computacionais com técnicas de planejamento de experimentos. Assim, foi possível: i) determinar os limites de controle de gráficos não paramétricos que monitorem simultaneamente as medidas de posição e escala para situações particulares; ii) a partir dos limites de controle calculados, estimar os erros tipo I e tipo II; e iii) comparar o desempenho desses gráficos com as cartas de controle estatístico de Shewhart para diferentes combinações de amostras (m, n) nas fases I e II. O método proposto foi aplicado em um processo de manufatura com o objetivo de identificar a combinação que minimize os erros tipo I e II. Com base nos resultados, observou-se que o gráfico de controle não paramétrico tem desempenho superior aos gráficos tradicionais de Shewhart quando a distribuição de probabilidade dos dados é assimétrica.

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“…Significant advances can also be seen in the literature regarding the development of new methods and strategies for SPC, such as models for auto-correlated data and multivariate processes (Costa & Castagliola, 2011;Costa & Machado, 2011;Dokouhaki & Noorossana, 2013;Franco et al, 2014;Leoni et al, 2015), control charts allowing for varying the sampling interval and the sample size (Reynolds et al, 1988;Reynolds, 1996 Yang et al, 2012;Mahadik, 2013), improvement in the performance of control charts by double sampling (Costa & Castagliola, 2011;Teoh et al, 2015;Inghilleri et al, 2015), the design of control charts that minimize operational costs (Michel & Fogliatto, 2002;Celano et al, 2011;Lupo, 2014;Franco et al, 2014), the integration of statistical process control and automatic/engineering process control, avoiding over adjustement of the process (Holmes & Mergen, 2011;Siddiqui et al, 2015); application of the Bernoulli control charts in the field of medicine (Szarka & Woodall, 2011), application of SPC to image data (Megahed et al, 2011;Wells et al, 2013), and strategies for monitoring the variability of small batches (Celano et al, 2012;Castagliola et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

A bibliometric analysis of 50 years of worldwide research on statistical process control

et al. 2016

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Resumo: Um crescente número de trabalhos sobre controle estatístico do processo (CEP) emergiu nos últimos cinquentaAbstract: An increasing number of papers on statistical process control (SPC) has emerged in the last fifty years, especially in the last fifteen years. This may be attributed to the increased global competitiveness generated by innovation and the continuous improvement of products and processes. In this sense, SPC has a fundamentally important role in quality and production systems. The research in this paper considers the context of technological improvement and innovation of products and processes to increase corporate competitiveness. There are several other statistical technics and tools for assisting continuous improvement and innovation of products and processes but, despite the limitations in their use in the improvement projects, there is growing concern about the use of SPC. A gap between the SPC technics taught in engineering courses and their practical applications to industrial problems is observed in empirical research; thus, it is important to understand what has been done and identify the trends in SPC research. The bibliometric study in this paper is proposed in this direction and uses the Web of Science (WoS) database. Data analysis indicates that there was a growth rate of more than 90% in the number of publications on SPC after 1990. Our results reveal the countries where these publications have come from, the authors with the highest number of papers and their networks. Main sources of publications are also identified; it is observed that the publications of SPC papers are concentrated in some of the international research journals, not necessarily those with the major high-impact factors. Furthermore, the papers are focused on industrial engineering, operations research and management science fields. The most common term found in the papers was cumulative sum control charts, but new topics have emerged and have been researched in the past ten years, such as multivariate methods for process monitoring and nonparametric methods.

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Projeto econômico de cartas adaptativas para monitoramento de processos

Abstract: Resumo Cartas

Cited by 9 publications

References 17 publications

Gestão pela qualidade - volume 2

Gestão pela qualidade - volume 2

Método de estimativa dos limites da carta de controle não paramétrica que monitora simultaneamente a média e variância

A bibliometric analysis of 50 years of worldwide research on statistical process control

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