Reliability Physics and Engineering: Time-To-Failure by J. W. McPherson PDF

By J. W. McPherson

ISBN-10: 1441963472

ISBN-13: 9781441963475

"Reliability Physics and Engineering" offers seriously vital info for designing and construction trustworthy within your budget items. The textbook comprises a number of instance issues of strategies. Included at the tip of each bankruptcy are workout problems and solutions. "Reliability Physics and Engineering" is an invaluable source for college students, engineers, and fabrics scientists.

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Example text

We want to obtain the best fitting for each model to the accelerated data and then see which model is more conservative (which model produces the shortest time-to-failure when the models are used to predict time-to-failure at much lower levels of stress). The time-to-failure TF data is plotted in Fig. 5. Both the exponential and powerlaw models tend to fit the actual accelerated data extremely well. However, even though both models tend to fit the accelerated data points extremely well, the two models give very different predictions for the time-to-failure (when the models are 7 Remember that one must convert the temperature from Centigrade to Kelvin.

One should always remember that the exponential model is more conservative. This may be very important to remember in the case of very high-reliability applications, if there is little understanding of the exact physics of failure. An understanding of failure mechanisms, and their physics of failure, can often be very helpful in helping one to decide on which model to use. 0E–01 10 100 1000 Fig. 1. Note that the two models fit the accelerated TF data extremely well at the higher values of stress.

In this example, 25 measurements were taken on the shear strength (in units of gm-f)4 of Au ball-bonds to aluminum pads on semiconductor chips. These 25 observed measurements (data points) were then ranked from smallest to largest value. 5 An unbiased estimate used for F in this text is: 1 Mean can be estimated: x50 = N xi /N, where N is the sample size. i=1 2 Standard deviation can be estimated: σ = N 1/2 (xi − x50 )2 /(N − 1) . 87%. 8×10−3 Newton. 5 A cumulative probability of exactly F=1 cannot be plotted.

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Reliability Physics and Engineering: Time-To-Failure Modeling by J. W. McPherson

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