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8. Assessing Product Reliability
8.4. Reliability Data Analysis
8.4.5. How do you fit system repair rate models?

8.4.5.3.

Exponential law model

Estimates of the parameters of the Exponential Law model can be obtained from either a graphical procedure or maximum likelihood estimation Recall from section 1 that the Exponential Law refers to a NHPP process with repair rate M'(t) = m(t) = EXP(alpha+beta*t) . This model has not been used nearly as much in industrial applications as the Power Law model, and it is more difficult to analyze. Only a brief description will be given here. 

Since the expected number of failures is given by 
M(t) = (1/beta)*EXP(alpha+beta*t) and ln M(t) = alpha-LN(beta) + beta*t, a plot of the cum fails versus time of failure on log-linear paper should roughly follow a straight line with slopebeta. Doing a regression fit of y = ln cum fails versus x = time of failure will provide estimates of the slopebeta and the intercept -alphalnbeta

Alternatively, maximum likelihood estimates can be obtained from the following pair of equations: 

SUM[i=1 to r]t(i) + r/betahat - r*T/(1-EXP(-beta*T)) = 0;    alphahat = LN{r*betahat/(EXP(-betahat*T) - 1)

The first equation is non-linear and must be solved iteratively to obtain the maximum likelihood estimate forbeta. Then, this estimate is substituted into the second equation to solve for the maximum likelihood estimate for alpha.

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