Sensitivity Analysis in Economics Based Test Strategy Planning

Dick, Jochen; Trischler, E.; Dislis, C.; Ambler, A.P.

doi:10.1007/978-1-4757-5048-5_10

Cited by 2 publications

(5 citation statements)

References 3 publications

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“…The part counting in (8)- (13) assumes that all false positives on good parts go through diagnosis and back into test without scrapping of parts in diagnosis or rework. The formulation is also only valid when f p < 1, Y in > 0 and Y beforetest > 0.…”

Section: Diagnosis and Reworkmentioning

confidence: 99%

“…Dick et al [13] point out that one of the main drawbacks in using economics models in general, and specifically for making test strategy decisions using economics models, is arriving at misleading results because of inaccurate inputs.…”

Section: Diagnosis and Reworkmentioning

confidence: 99%

“…To accommodate uncertainties in input data, the model has been implemented within a Monte Carlo analysis framework similar to that in [13]. Each non-integer input can have a designated distribution type (triangular distributions are used as an example in Section 4).…”

Section: Diagnosis and Reworkmentioning

confidence: 99%

“…inn appearing in (4) is defined in(13). The total cost of all the parts (including scrapped parts) is the sum of C 1 through C 4 .…”

mentioning

confidence: 99%

See 3 more Smart Citations

A new test/diagnosis/rework model for use in technical cost modeling of electronic systems assembly

Trichy

Sandborn²,

Raghavan³

et al.

Proceedings International Test Conference 2001 (Cat. No.01CH37260)

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This paper presents a test/diagnosis/rework analysis model for use in technical cost modeling of electronic assemblies. The approach includes a model of test operations characterized by fault coverage, false positives, and defects introduced in test, in addition to rework and diagnosis operations that have variable success rates and their own defect introduction mechanisms. The model can accommodate an arbitrary number of rework attempts on any given assembly and can be used to optimize the fault coverage and rework investment during system tradeoff analyses. The model's implementation allows all inputs to the model to be represented as probability distributions thereby accommodating inevitable uncertainties in input data present during tradeoff activities and uses Monte Carlo methods to determine model outputs.

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Section: Diagnosis and Reworkmentioning

confidence: 99%

Section: Diagnosis and Reworkmentioning

confidence: 99%

Section: Diagnosis and Reworkmentioning

confidence: 99%

“…inn appearing in (4) is defined in(13). The total cost of all the parts (including scrapped parts) is the sum of C 1 through C 4 .…”

mentioning

confidence: 99%

See 2 more Smart Citations

A new test/diagnosis/rework model for use in technical cost modeling of electronic systems assembly

Trichy

Sandborn²,

Raghavan³

et al.

Proceedings International Test Conference 2001 (Cat. No.01CH37260)

View full text Add to dashboard Cite

show abstract

“…Thus, our work can be thought of as providing the input into the test optimization process. It is important to do this well; it is recognized that the optimal test sequence can be highly sensitive to test model parameter values . We do this for the imperfect test and repair model of Fisher et al .…”

Section: Introductionmentioning

confidence: 99%

Estimating production test properties from test measurement data

Wilson

Goyal²

2011

Appl Stoch Models Bus & Ind

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A complex sequence of tests on components and the system is a part of many manufacturing processes. Statistical imperfect test and repair models can be used to derive the properties of such test sequences but require model parameters to be specified. We describe a technique for estimating such parameters from typical data that are available from past testing. A Gaussian mixture model is used to model the wide variety of statistical properties of test data, including outliers, multi-modality and skewness, from which test properties are derived. Model fitting is through a Bayesian approach, implented by Markov chain Monte Carlo.

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Sensitivity Analysis in Economics Based Test Strategy Planning

Cited by 2 publications

References 3 publications

A new test/diagnosis/rework model for use in technical cost modeling of electronic systems assembly

A new test/diagnosis/rework model for use in technical cost modeling of electronic systems assembly

Estimating production test properties from test measurement data

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