Arrhenius and the temperature dependence of non‐constant failure rate

Blanks, Henry S.

doi:10.1002/qre.4680060408

Cited by 24 publications

(10 citation statements)

References 9 publications

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“…Blanks [30] in a similar vein has questioned the validity of the Arrhenius relation when nonconstant failure rates prevail. He suggests that the temperature-dependent rate of equipment failure is less than that predicted by the Arrhenius AF when the hazard rate decreases with time.…”

Section: Is Arrhenius Erroneous?mentioning

confidence: 99%

The Mathematics of Failure and Reliability

Ohring

Kasprzak²

2015

Reliability and Failure of Electronic Materials and Devices

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Section: Is Arrhenius Erroneous?mentioning

confidence: 99%

The Mathematics of Failure and Reliability

Ohring

Kasprzak²

2015

Reliability and Failure of Electronic Materials and Devices

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“…The Arrhenius law is a widespread model in the electronic packaging industry to relate failure rate and temperature [9]. We assume that the junction temperature of the module in the center represents the average junction temperature of the modules on PWB.…”

Section: ) Heat Conduction In Pwbmentioning

confidence: 99%

“…Plated through-hole vias are treated as conducting fibers in the insulator matrix. The equivalent thermal conductivity in the Z-direction, , is given by (9) where is the thermal conductivity of the metal used for via plating (in this case, copper), is the thermal conductivity of the insulator (in this case, epoxy glass), is the sum of the cross-section area of the via metal per unit area of PWB.…”

Section: ) Heat Conduction In Pwbmentioning

confidence: 99%

Application of multiobjective optimization in selection of printed wiring boards

Li¹,

Palusinski

2003

IEEE Trans. Adv. Packag.

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This paper presents an application of multiobjective optimization in optimal selection of number of signal layers in printed wiring board (PWB). The criteria considered in optimization are: cost, electrical performance, and reliability. The reliability of system is influenced by the operating temperature, which is determined by the power dissipated in parts placed on the board, ambient temperature, and cooling technology. In evaluating cooling and calculation of junction temperature both heat conduction through the board and forced air cooling are considered. Designers have to deal with multiple, conflicting criteria because of variety of requirements that packaging should meet. However, sophisticated methods developed for multiobjective optimization are not yet used in packaging design. This paper describes some of the methods used in solving multicriteria optimization and gives an example of application to design of PWB.The weighting method is applied to find the optimal solution first. The graphical form of optimality of different weights for different criteria is presented. The distance based methods, which include 1 -distance, 2 -distance, -distance, and the geometric distance method, are also applied to determine the optimal number of signal layers. The results from different methods are compared and discussed.Index Terms-Design of printed wiring board, distance based methods, multicriteria optimization, multilayer board, weighting method.

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“…Even though various functional relationships between failure rate and temperature in electronic components have been suggested (Wong [18]), according to Blanks [19], the Arrhenius relation is the most widespread model among practitioners in the electronic packaging industry. In this study, the failure rate of electronic component " " is estimated using the Arrhenius relation as (1) Here and are constants associated with the thermal sensitivity of the electronic component, while is the maximum temperature of component " ."…”

Section: Problem Definitionmentioning

confidence: 99%

Multiobjective optimal placement of convectively cooled electronic components on printed wiring boards

Queipo

Humphrey

Ortega

1998

IEEE Trans. Comp., Packag., Manufact. Technol. A

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This paper presents a solution methodology for multiobjective optimization problems in the context of models for the placement of components on printed wiring boards (PWB's). The methodology combines the use of a flow and heat transfer solver, a genetic algorithm for the adaptive search of optimal or near-optimal solutions, and a multiobjective optimization strategy [Pareto optimization or multiattribute utility analysis (MUA)]. Using as the optimization criterion the minimization of an estimate of the failure rate of the system of components due to thermal overheating (via an Arrhenius relation), the effectiveness of the present solution methodology is demonstrated by reference to a case with known optimal solutions. The results obtained using the same solution methodology for a multiobjective optimization problem (a variation of the case study) involving the minimization of the aforementioned total failure rate of the system as well as the minimization of the total wiring length (given some interconnectivity requirements) are presented and discussed for both Pareto optimization and MUA.

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Arrhenius and the temperature dependence of non‐constant failure rate

Cited by 24 publications

References 9 publications

The Mathematics of Failure and Reliability

The Mathematics of Failure and Reliability

Application of multiobjective optimization in selection of printed wiring boards

Multiobjective optimal placement of convectively cooled electronic components on printed wiring boards

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