See how to use JMP to make reliability predictions. Fit life distributions for non-repairable systems, perform accelerated life tests and measure event recurrence for repairable systems. Posted October 2, 2015.
Presenter: Erich Gundlach
See how to use JMP to make reliability predictions. Fit life distributions for non-repairable systems, perform accelerated life tests and measure event recurrence for repairable systems. Posted October 2, 2015.
Presenter: Erich Gundlach
The presenter uses an electronic motor case study to show how to fit basic life distributions to failure data. He ignores the failure cause and demonstrates how to run and compare life distributions, examine goodness of fit statistics for various distributions, select a good distribution, and use Profilers to examine the probability of failure under different conditions. He shows how to fit competing risk mixture distributions to estimate the probability that a given observation fails due to the cause represented by each of the component mixture distributions.
The presenter uses capacitor data to show how to use accelerating conditions to predict pseudo failure times, use these times to estimate life distribution and predict the probability of failure under different operating conditions. He cautions to make sure that the accelerating conditions can extrapolate back to normal operating conditions.
The presenter uses generic data to perform recurrence analysis for repairable systems. He examines the frequency and expected cost of failure over time. He models the results and predicts the probability of failures under different conditions.