The failure rate function estimated from parameter drift measurements

Møltoft, Jørgen

doi:10.1016/0026-2714(80)90003-7

Cited by 13 publications

(5 citation statements)

References 2 publications

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“…If it is below the memory is rejected. 3i G. Bosch and J. McNtoft: "Algorithms for the Estimation of Reliability from parameter measurements "1 a, 14 For the assistance of parameter screening methods two algorithms which have been published recently, shall be mentioned.…”

Section: Reliability Indicator Methods Assessmentmentioning

confidence: 99%

Reliability Assessment and Screening by Reliability IndicatorMethods

Møltoft

1983

Active and Passive Electronic Components

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Built-in flaws in electronic components have been recognized as a serious cause of failure. They are difficult to screen away by conventional methods because the times-to-failures for component working in systems are often rather long and because accelerated burn-in may screen by the wrong failure mechanisms. As an alternative, the concept and possible use of reliability indicator methods are discussed and some recently developed methods described.

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Section: Reliability Indicator Methods Assessmentmentioning

confidence: 99%

Reliability Assessment and Screening by Reliability IndicatorMethods

Møltoft

1983

Active and Passive Electronic Components

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“…The time-to-failure calculated from equation (9) for TFRs (ESL 2911) and from equation (6) for TFRs (ESL 3111) are given in Table II. …”

Section: Introductionmentioning

confidence: 99%

“…2 The test results obtained are given in Table I. The X 2 test of goodness-of-fit is used for the normal distribution, 4 and, in Table I, From the drift function, equation (7), equation (6) for TFRs (ESL 2911) can be written:-…”

Section: Introductionmentioning

confidence: 99%

“…is the standard normal cumulative distribution function. From equation (6) it is easy to calculate the time tp at which the parameter drift will reach the limits (a,/3) for (1 P).100% of the components tested, or alternatively the percentage of the failures in a given period of time.…”

Section: Introductionmentioning

confidence: 99%

“…The calculations of the time-to-failure of TFRs (ESL 2911) can be performed using equation (9) and that of the TFRs (ESL 3111) with equation (6), since the drift function, equation (8), is linear.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Model for reliability prediction of thick film resistors

1984

Microelectronics Reliability

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A model for time-to-failure prediction based on component parameter drift is described. The idea for creation of this model is based on the influence of time-dependent random and non random factors on the distribution of the random variable.The reliability interpretation of the data from thick film resistor ageing tests has been completed with the model developed. Two different drift functions are described for two ruthenium-based thick film methods with equal resistivity 10s2/square.

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The organization of a study of the field failure of electronic components

Campbell

Hayes

Hetherington³

1987

Quality & Reliability Eng

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This paper describes the organization that has been evolved for the collection and analysis of field failure data. A summary breakdown is given of the data collection organization, the Data Format and the methodology of Data Analysis. Preliminary studies show the system is working. The concept of superpopulation has been established in order to judge the relative importance of data as it is accumulated.

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The failure rate function estimated from parameter drift measurements

Cited by 13 publications

References 2 publications

Reliability Assessment and Screening by Reliability IndicatorMethods

Reliability Assessment and Screening by Reliability IndicatorMethods

Model for reliability prediction of thick film resistors

The organization of a study of the field failure of electronic components

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