An overview of theory and practice on process capability indices for quality assurance

Wu, Chien‐Wei; Pearn, W. L.; Kotz, Samuel

doi:10.1016/j.ijpe.2008.11.008

Cited by 277 publications

(140 citation statements)

References 95 publications

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“…Segundo Montgomery (2004) e Kotz e Johnson (1993) se a distribuição dos valores dos dados não é normal, então, as afirmações sobre falhas esperadas do processo atribuídas a um valor particular de índices de capacidade de processo tais como a Capacidade do Processo (Cp) ou a Capacidade Efetiva do Processo (Cpk), descritos por Pearn e Liao (2005), podem não ser verdadeiras, o que é particularmente grave, pois Wu et al (2009) definem estes índices como um valor numérico da capacidade de um processo se encontrar dentro de uma tolerância definida. Assim o intervalo de confiança do índice fica comprometido (ZIMMER et al, 2001).…”

Section: Introductionunclassified

Avaliação da distribuição de sementes por uma semeadora de anel interno rotativo utilizando média móvel exponencial

Albiero¹,

Maciel²,

Milan³

et al. 2012

Rev. Ciênc. Agron.

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Resumo -Conceitos de qualidade cada vez mais se tornam essenciais para a sobrevivência da empresa agrícola, pois a importância do aprimoramento das operações agrícolas se faz necessária para a obtenção de resultados viáveis economicamente, ambientamente e socialmente. Uma das dimensões da qualidade é conseguir de conformidade, ou seja, a garantia de execução exata do que foi planejado para atender aos requisitos dos clientes em relação a um determinado produto ou serviço. Os objetivos deste trabalho são avaliar a distribuição longitudinal entre sementes de uma semeadora de anel interno rotativo, e propor a utilização da metodologia estatística da Média Móvel Exponencialmente Ponderada (MMEP) como alternativa para o controle de qualidade da semeadura, quando não há normalidade da distribuição dos dados. Os resultados demonstraram que a MMEP é adequada para a avaliação da qualidade da distribuição longitudinal de sementes, pois concordou com os dados apresentados na estatística descritiva, o que lhe credencia para avaliação de distribuições não normais. Palavras-chave -Uniformidade de distribuição. Controle de Qualidade. Média móvel.Abstract -Quality concepts are essentials for survivor of agricultural companies, therefore, the importancy of improvement of agricultural process is necessary for to get results economically, environmentally and socially viables. One quality dimension is to get a compliance quality, ie, ensure the exact execution than was planned. The subject of this paper is evaluable at longitudinal distribution between seed of a internal ring seeder. The subject of this paper is to evaluate at longitudinal distribution between seed distributed for a internal ring seeder and to propose the use of statistical methodology exponentially weighted moving average (MMEP) like alternative for the quality control of seeders, when there is not normality in data. The results showed that the MMEP is adequate for quality evaluation of longitudinal distribution between seeds, as agreed with the data of descriptive statistic.

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Section: Introductionunclassified

Avaliação da distribuição de sementes por uma semeadora de anel interno rotativo utilizando média móvel exponencial

Albiero¹,

Maciel²,

Milan³

et al. 2012

Rev. Ciênc. Agron.

View full text Add to dashboard Cite

show abstract

“…Process capability analysis is a well-defined tool within statistical process control techniques that continuously improves quality and productivity [9]. The first aim for using PCA is to obtain information about the process and to determine if the process can be improved [3].…”

Section: Process Capability Analysismentioning

confidence: 99%

Gömleklik Kumaş için Proses Yeterlilik İndekslerinin Belirlenmesi

Akcan¹

2016

Çukurova Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi

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Organizations use process capability analysis to produce their products within specification limits for regular manufacturing. Process capability indices, C p (process potential indices) and C pk (process capability indices), are used as capability measures. In this study, process capability analysis and process capability indices are discussed in the context of a textile factory that produces shirting fabrics in Turkey. In this factory, it is desired that the amount of wastage fabric does not exceed the upper limit that identified from production manager. If the amount of wastage fabric increases, the number of unsatisfied customers will also increase. And, this situation is caused increasing cost and decreasing competitiveness for factory. For these reasons, C p and C pk indices were calculated for the textile factory. As a consequence of this study, we discovered that the process was inadequate precautions must be undertaken to decrease the amount of wastage fabric. Furthermore, the fabric faults which cause wastage fabric and the reasons for the process' inadequacies were also investigated.

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“…In summary, as long as the type of distribution is known, distribution parameter can be estimated by maximum likelihood estimation, and then FIM may be calculated by equation (5) or equation (6). Lastly, the confidence interval of the maximum likelihood estimator can be obtained by equation (8).…”

Section: Analysis Of Confident Intervalmentioning

confidence: 99%

“…Nonetheless, this method will overestimate the product yield of suppliers. In addition, some Correspondence: kkgukai@vip.qq.com researchers propose to transform the truncated sample by data transformation [2,3], and then calculate process capability index [4][5][6] by the coded data. Actually, such a transformation will alert the distribution of the original data and cause a non-negligible calculation error [7].…”

Section: Introductionmentioning

confidence: 99%

The yield estimation of semiconductor products based on truncated samples

Jia

You

et al. 2013

Int. J. Metrol. Qual. Eng.

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Abstract. Product yield reflects the potential product quality and reliability, which means that high yield corresponds to good quality and high reliability. Yet consumers usually couldn't know the actual yield of the products they purchase. Generally, the products that consumers get from suppliers are all eligible. Since the quality characteristic of the eligible products is covered by the specifications, then the observations of quality characteristic follow truncated normal distribution. In the light of maximum likelihood estimation, this paper proposes an algorithm for calculating the parameters of full Gaussian distribution before truncation based on truncated data and estimating product yield. The confidence interval of the yield result is derived, and the effect of sample size on the precision of the calculation result is also analyzed. Finally, the effectiveness of this algorithm is verified by an actual instance.

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An overview of theory and practice on process capability indices for quality assurance

Cited by 277 publications

References 95 publications

Avaliação da distribuição de sementes por uma semeadora de anel interno rotativo utilizando média móvel exponencial

Avaliação da distribuição de sementes por uma semeadora de anel interno rotativo utilizando média móvel exponencial

Gömleklik Kumaş için Proses Yeterlilik İndekslerinin Belirlenmesi

The yield estimation of semiconductor products based on truncated samples

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