On the relationship between semiconductor manufacturing volume, yield, and reliability

Siddiqui, J. J.; Ortega, John E.; Albus, Brian

doi:10.1109/irps.2017.7936409

Cited by 3 publications

(5 citation statements)

References 12 publications

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“…Entropy refers to the degree of confusion within the system [ 14 ]. If entropy is 0, the molecules inside the system is are uniformly distributed.…”

Section: Uncertainty Evaluation Of Assembly Processmentioning

confidence: 99%

“…Previously, some attempts have been made to extend defect models to estimate reliability. At first, a simple time-independent Poisson reliability was obtained assuming directly that the number of nonfatal defects corresponded to the fatal defects following a Poisson distribution [ 13 , 14 , 15 ]. All models implicitly assumed that the number of fatal defects is independent of the number of the latent defects in a device.…”

Section: Introductionmentioning

confidence: 99%

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Uncertainty Evaluation in Multistage Assembly Process Based on Enhanced OOPN

Huang

Dai

Mou

et al. 2018

Entropy

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This study investigated the uncertainty of the multistage assembly process from the viewpoint of a stream of defects in the product assembly process. The vulnerable spots were analyzed and the fluctuations were controlled during this process. An uncertainty evaluation model was developed for the assembly process on the basis of an object-oriented Petri net (OOPN) by replacing its transition function with a fitted defect changing function. The definition of entropy in physics was applied to characterize the uncertainty of the model in evaluating the assembly process. The uncertainty was then measured as the entropy of the semi-Markov chain, which could be used to calculate the uncertainty of a specific subset of places, as well as the entire process. The OOPN model could correspond to the Markov process because its reachable token can be directly mapped to the Markov process. Using the steady-state probability combined with the uncertainty evaluation, the vulnerable spots in the assembly process were identified and a scanning test program was proposed to improve the quality of the assembly process. Finally, this work analyzed the assembly process on the basis of the uncertainty of the assembly structure and the variables of the assembly process. Finally, the case of a certain product assembly process was analyzed to test the advantages of this method.

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“…Entropy refers to the degree of confusion within the system [ 14 ]. If entropy is 0, the molecules inside the system is are uniformly distributed.…”

Section: Uncertainty Evaluation Of Assembly Processmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Uncertainty Evaluation in Multistage Assembly Process Based on Enhanced OOPN

Huang

Dai

Mou

et al. 2018

Entropy

View full text Add to dashboard Cite

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“…The resulting parameters ρ 1 and ρ 2 are real values if c 2 ∈ [0. 5,1]. This paper assumes that the total defect is D; each time there is a probability ρ 1 of the first type of defects (component solderability), there is a probability ρ 2 of the second type of defects (electro migration), where ρ 1 + ρ 2 = 1.…”

Section: Quantification Defines Defectmentioning

confidence: 99%

“…Previously, there were some attempts to extend defect models to estimate reliability. A simple time-independent Poisson reliability was obtained by directly assuming that the number of nonfatal defects is proportional to the number of fatal defects following a Poisson distribution [4][5][6]. But only cases of the distribution of defects following a certain law are analyzed and they were not completely applied to the assembly process.…”

Section: Introductionmentioning

confidence: 99%

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Screening Scheme Evaluation of the Assembly Process Based on the Stress-Strength Model and Defect Stream Analysis

Huang

Dai

Liu

et al. 2018

Entropy

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During the assembly process, there are inevitable variations and noise factors in the material properties, process parameters and screening scheme, which may affect the quality of the product. Using the stress-strength model, an evaluated screening scheme method, by analyzing the variation of the defect density in the assembly process, is proposed and discussed. The influence of screening stress on product defects is considered to determine the screening scheme. We performed the defect stream analysis by calculating the recursive relations of residual defect density under multi-stress conditions. We find that the probability density function, which shows the defect changing process from latent to dominant relative to the time process, agrees very well with the historical data. We also calculate the risk as the entropy of the assembly task. Finally, we verify our method by analyzing the assembly process of a certain product.

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