Case studies in system burn-in

Jensen, Finn

doi:10.1016/0143-8174(82)90019-1

Cited by 6 publications

(4 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A concern in burn‐in policy is to seek a DR that maximizes the economic benefits 2 . Based on this principle, we develop an economic cost model, consisting of the following components:

C_{α}

: the cost of Type I error, which is the per‐unit cost of misclassifying a normal unit as weak;

C_{β}

: the cost of Type II error, which is the per‐unit cost of misclassifying a weak unit as normal; C op : the cost of operating the burn‐in procedure (from 0 up to t b ) for each unit; C mea : the cost of collecting data for each unit; n : the total number of units subject to the burn‐in test; p : the proportion of weak units. …”

Section: Optimal Burn‐in Policy Based On a Set Of Cutoff Pointsmentioning

confidence: 99%

See 1 more Smart Citation

Optimal burn‐in policy based on a set of cutoff points using mixture inverse Gaussian degradation process and copulas

Morita

Tomazella

Ferreira

et al. 2021

Appl Stoch Models Bus & Ind

View full text Add to dashboard Cite

Burn‐in tests have been discussed extensively in the reliability literature, wherein we operate items until high degradation values are observed, which could separate the weak units from the normal ones before they get to the market. This concept is often referred to as a screening procedure, and it involves misclassification errors. Commonly, the underlying degradation process is assumed to be a Wiener or a gamma process, based on which several optimal burn‐in policies have been developed in the literature. In this article, we consider the mixture inverse Gaussian process, which possesses monotone degradation paths and some interesting properties. Under this process, we present a decision rule for classifying a unit under test as normal or weak based on burn‐in time and a set of cutoff points. Then, an economic cost model is used to find the optimal burn‐in time and the optimal cutoff points, when the estimation of model parameters is based on an analytical method or an approximate method involving copula theory. Finally, an example of a real dataset on light amplification by stimulated emission of radiations, well known in the reliability literature, is used to illustrate the model and the inferential approach proposed here.

show abstract

“…A concern in burn‐in policy is to seek a DR that maximizes the economic benefits 2 . Based on this principle, we develop an economic cost model, consisting of the following components:

C_{α}

: the cost of Type I error, which is the per‐unit cost of misclassifying a normal unit as weak;

C_{β}

Section: Optimal Burn‐in Policy Based On a Set Of Cutoff Pointsmentioning

confidence: 99%

“…These failures, which usually happen in a small proportion among the manufactured items, are generally caused by manufacturing defects and lead to high warranty and replacement costs. Diverse burn‐in policies have been discussed in the degradation literature; see, for example, Jensen, 2 Kuo, 3 and Leemis and Beneke 4 …”

Section: Introductionmentioning

confidence: 99%

Optimal burn‐in policy based on a set of cutoff points using mixture inverse Gaussian degradation process and copulas

Morita

Tomazella

Ferreira

et al. 2021

Appl Stoch Models Bus & Ind

View full text Add to dashboard Cite

show abstract

“…A concern in burn-in policy is to find a decision rule that maximizes the economic benefits (JENSEN, 1982). Based on this principle, we design an economic cost model, consisting of the following components:…”

Section: Optimal Burn-in Time and Cutoff Pointmentioning

confidence: 99%

“…Such failures that generally occur in a small proportion among the manufactured products are caused by manufacturing defects and lead to high warranty and replacement costs. Many burn-in policies have been extensively studied in the degradation literature; see for example Jensen (1982), Kuo (1984) and Leemis and Beneke (1990).…”

Section: Introduction 11 Introduction and Bibliographical Reviewmentioning

confidence: 99%

Degradation modeling for reliability analysis with time-dependent structure based on the inverse gaussian distribution

Morita¹

View full text Add to dashboard Cite

As técnicas convencionais de análise de confiabilidade são voltadas para a ocorrência de falhas ao longo do tempo. Contudo, em determinadas situações nas quais a ocorrência de falhas é pequena ou quase nula, a estimação das quantidades que descrevem os tempos de falha fica comprometida. Neste contexto foram desenvolvidos os modelos de degradação, que possuem como dado experimental não a falha, mas sim alguma característica mensurável a ela atrelada. A análise de degradação pode fornecer informações sobre a distribuição de vida dos componentes sem realmente observar falhas. Assim, nesta tese nós propusemos diferentes metodologias para dados de degradação baseados na distribuição gaussiana inversa. Inicialmente, nós introduzimos o modelo de taxa de deterioração gaussiana inversa para dados de degradação e um estudo de suas propriedades assintóticas com dados simulados. Em seguida, nós apresentamos um modelo de processo gaussiano inverso com fragilidade considerando que a fragilidade é uma boa ferramenta para explorar a influência de covariáveis não observadas, e um estudo comparativo com o processo gaussiano inverso usual baseado em dados simulados foi realizado. Também mostramos um modelo de mistura de processos gaussianos inversos em testes de burn-in, onde o principal interesse é determinar o tempo de burn-in e o ponto de corte ótimo para separar os itens bons dos itens ruins em uma linha de produção, e foi realizado um estudo de má especificação com os processos de Wiener e gamma. Por fim, nós consideramos um modelo mais flexível com um conjunto de pontos de corte, em que as probabilidades de má classificação são estimadas através do método exato com distribuição gaussiana inversa bivariada ou em um método aproximado baseado na teoria de cópulas. A aplicação da metodologia foi realizada com três conjuntos de dados reais de degradação de componentes de LASER, rodas de locomotivas e trincas em metais.Palavras-chave: Análise de degradação, Distribuição gaussiana inversa, Processo gaussiano inverso, Fragilidade, Testes de burn-in.

show abstract

Mixed hazard models and their applications

Yuan

Shih

1991

Reliability Engineering & System Safety

View full text Add to dashboard Cite

Case studies in system burn-in

Cited by 6 publications

References 3 publications

Optimal burn‐in policy based on a set of cutoff points using mixture inverse Gaussian degradation process and copulas

Optimal burn‐in policy based on a set of cutoff points using mixture inverse Gaussian degradation process and copulas

Degradation modeling for reliability analysis with time-dependent structure based on the inverse gaussian distribution

Mixed hazard models and their applications

Contact Info

Product

Resources

About