A prediction based design-for-reliability toot

Edson, B.; Tian, Xijin

doi:10.1109/rams.2004.1285484

Cited by 4 publications

(1 citation statement)

References 1 publication

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“…All system requirements should be known by manufacturers, especially for military product, many times the poor communication of double staffed critical design tolerances have caused some of the satellites and probes not to function properly at a very large cost to the manufacturer. There is a good tool that is available to bridge the gap between the customer and the supplier that is called quality function deployment (QFD), QFD [16][17][18][19][20][21] can provide a systematic structure that forces the customer to think about the "wants", which are then converted by the structure to needs and then presented to the next immediate supplier in an organized fashion. Second, one important item that the customer needs to find out about is the suppliers design rule.…”

Section: The Customer Role In Birmentioning

confidence: 99%

Building-in Reliability for VLSI

Zou

Yao

2006

2006 International Conference on Electronic Materials and Packaging

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Building-in Reliability (BIR) was introduced in the early of 1990's. It is a methodology to manufacture highly reliable IC by minimizing and eliminating the sources of product unreliability in the beginning of a new product process. The characteristic of integrated reliability about BIR diffuses the responsibility for reliability into the whole team, including not only the process/ reliability/ characterization engineers, but also the applied research engineers and the customers who use integrated circuits. It's well known that the quality and reliability are defined by the customer, not by the manufacturers. So the customer's role in BIR is very important, especially the responsibilities of establishing good communications with the manufacturer and returning all failures to the manufacturer. The quality function deployment (QFD) and qualified manufacturer's list (QML) can help the customer take his responsibilities. In addition, nowadays little progress has been made in charactering the reliability of the future high reliability of VLSI after using the BIR approach. Small-sample statistical theory, especially for support vector machines (SVM) will be attempted to assess the reliability of VLSI.

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Section: The Customer Role In Birmentioning

confidence: 99%

Building-in Reliability for VLSI

Zou

Yao

2006

2006 International Conference on Electronic Materials and Packaging

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Minimize system failure rate considering variations of electronic components lifetime data [PCB design for reliability]

Jin

Xiong

Wang³

Proceedings of 2005 International Conference on Asian Green Electronics, 2005. AGEC.

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Minimize system reliability variability based on six-sigma criteria considering component operational uncertainties

Jin

su²

Annual Reliability and Maintainability Symposium, 2005. Proceedings.

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Temperature and electrical stresses are important factors in affecting the lifetime of electronic devices. In field applications, device temperature and electrical stresses are usually neither constant nor consistent in the system. Many existing reliability prediction models often assume the temperature and electrical stresses as deterministic values in estimating the failure rate of electronic devices in a printed circuit board (PCB). A PCB consists of multiple identical electronic devices such as resistors, capacitors, and ICs etc, and the device temperature varies from location to location due to difference of power consumption and cooling efficiency. For the same type of device, electrical stresses often vary in different subcircuities even though they are used in the same board.This paper proposes a stochastic reliability prediction model to estimate electrical device failure rates that explicitly incorporate the variations of the temperature and electrical stresses. For the same type of electrical devices, the temperature and the electrical stress factors are treated as stochastic values, not deterministic numbers. The mean and variance of the factors are derived based on the device temperature distribution and the electrical stress profile. Then the overall PCB failure rate is estimated by appropriately aggregating all device failure rates. Finally, the confidence intervals for the PCB failure rate are obtained based on sixsigma criteria. The method was applied to the design of a broadband analog board.

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A prediction based design-for-reliability toot

Cited by 4 publications

References 1 publication

Building-in Reliability for VLSI

Building-in Reliability for VLSI

Minimize system failure rate considering variations of electronic components lifetime data [PCB design for reliability]

Minimize system reliability variability based on six-sigma criteria considering component operational uncertainties

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