Accelerated life testing, Advanced Statistics

Accelerated life Testing

A set of methods or techniques which are intended to ensure product reliability during the time of design and manufacture in which stress is applied to promote the failure. The applied stresses might be vibration, temperature, shock etc. In order to make a valid inference about the normal lifetimeof the system from the accelerated data (accelerated in the sense that a shortened time to the failure is implied), it is essential to know the association between time to failure and applied stress. Frequently parametric statistical models of the time to failure and of the manner in which the stress accelerates aging are used.





 

Posted Date: 7/25/2012 4:38:03 AM | Location : United States







Related Discussions:- Accelerated life testing, Assignment Help, Ask Question on Accelerated life testing, Get Answer, Expert's Help, Accelerated life testing Discussions

Write discussion on Accelerated life testing
Your posts are moderated
Related Questions
Evaluate the following statistical arguments. Begin by identifying the sample, population, and the property which is being investigated. Do these arguments sound acceptable? Would

This is the powerful visualization tool for studying how the response relies on an explanatory variable given the values of other explanatory variables. The plot comprises of a num

relevancy of time series in business management


Bayes factor : A summary of evidence for the modelM1 against the another modelM0 provided by the set of data D, which can be used in the model selection. Given by the ratio of post

sfdgfdg

Confounding:  A procedure observed in some factorial designs in which it is impossible to differentiate between some main effects or interactions, on the basis of the particular d

Reliability theory is the theory which attempts to determine the reliability of the complex system from knowledge of the reliabilities of the components. Interest might centre on

The problematic and enigmatic theory of an inference introduced by the Fisher, which extracts a probability distribution for the parameter on the basis of the data without having f

The measure of the degree to which the particular model differs from the saturated model for the data set. Explicitly in terms of the likelihoods of the two models can be defined a