See how to:
- Understand the kinds of problems are addressed by reliability tools
- Problems where a product (or process) is repeatedly stressed, eventually leading to failures and stressor could be anything ( e.g., voltage cycles, mechanical loadings, Car washings, Start/stop cycles on a motor)
- Problems where a product (or process) is repeatedly stressed, leading to Degradation in performance (e.g., tire wear vs. mileage, HVAC efficiency over number of cycles, adhesion strength over time, drug shelf life)
- Consider issues addressed by Reliability Analysis
- When will it break?
- How long do certain employees stay and when will they leave?
- How long do patients survive based on medical treatments?
- What is the pattern for credit card churn?
- In Pharma, how do I set my expiration date?
- How long of a warranty should I offer customers?
- What is a typical repair time?
- How can I put pieces together to give best reliability of a system of parts?
- Understand censoring used in analysis
- Sometimes we know exactly when something fails
- Sometimes we end a test before all parts have failed and the "still alive" parts are called "Right Censored", or often just "Censored"
- Sometimes we check parts periodically during a test, find one that failed, and we don't know exactly when it failed (just that it failed before the inspection) and These are called "Left Censored"
- Sometimes we check parts periodically and know that at time T the part was functioning, but a T+1 the part had failed and this is called "Interval Censoring"
- Use Life Distribution to analyze reliability with or without multiple failure causes
- Interpret Event Plots and Parametric Estimates – Exponentia
- Profile Behaviors using Distribution, Quantile, Hazard and Density Profilers
- Perform Accelerated Life Testing for situations where it takes too long for a product (e.g., flourescent light bulbs) to fail so we can’t conduct a reasonable-length reliability test
- Use accelerator (e.g., temperature), to run test units at accelerant conditions and extrapolate back to a "standard" condition
- Analyze and interpret results from one accelerator at a time using Fit Life by X.
- Perform Degradation Analysis on substances that degrade, change in potency or increase in impurities increase over time
- Interpret Overlay Plot, generate report for current mode, interpret Inverse Prediction Plot
- Analyze stability for determining product expiration dates using Stability Tests
- Perform Destructive Degradation when test for the Critical to Quality metric requires destruction of the test sample
Questions and answers that followed the live demo Jerry Fish @JerryFish and Don McCormack @DonMcCormack:
Q: What does ‘Censor’ indicate in the Life Distribution Analysis?
A: Censor indicates the object is still functioning when last observed.
Q: What will change if we select a different censor code?
A: When you select a different censor code, you change the observations that correspond to censored observations.
Q: For Life Distribution, why is the hazard high at low kilocycles?
A: Hazard is the ratio of the cumulative failures to the probability of failure. I suspect it is large because the probability (i.e., the denominator) is very small.
Q: I see a tab that says "Acceleration Factor" as part of Accelerated Life Test. Does JMP calculate your acceleration factor for you based on experimental data!? If so, that's AMAZING!
A: Yes, it is based on the data and the assumptions you make about the acceleration factor (e.g., it is Arhhenius).
Q: Is the accelerated life testing software validated to use with drug stability studies for FDA?
A: JMP has been numerically tested using the NIST data sets. The Degradation platform would be the place to start for stability analysis (unless you’re comfortable with fitting linear models with Fit Model). The ICH Q1E guidelines were used for the Stability part of Degradation platform and documented in our quality statement talking about OQ and IQ:
Q: Would the 'X' section be used to do multivariate degradation?
A: In the platforms that take multiple Xs, you can model a (single) response with multiple predictors. There are certain reliability platforms that allow you to do that. Fit Parametric is the most general of them.
Q: How do we get to the Stability Studies analysis?
A: It’s under Degradation (Analyze>Reliability and Stability>Degradation), the third tab in the initial dialog.
Q: Is there a way to determine if a new form of degradation is kicking in at higher temps?
A: Possibly. In these cases, you may be dealing with mixtures. Life Distribution lets you fit mixtures.
Q: If your equipment only has discrete settings, then that would be the correct way to do the analysis, right?? 14:49
A: Yes, that is one way to do the analysis.
Q: From a QA perspective do you have documentation to support your JMP analysis process establishing shelf life for a pharmaceutical drug product which FDA has approved.
A: In terms of shelf life, we’re following ICH Q1E guidelines.
Q: Is it possible to do Nevada Chart Analysis in JMP?
A: Yes. In Reliability Forecast, the Reliability Forecast red triangle menu contains the option Save Data in Time to Event Format, which saves Nevada or Dates data in a Time to Event formatted table.
Q: Regarding Confidence Interval, I know JMP 16 can change the CI in the life distribution and in the Fit Life by X. Is there a way to change the CI in the Parametric survival fit? The default is 95%, some cases, I might want to change it to other values, for example, 75%. I don't see this option in Fit Life by X.
A: In Fit Parametric Survival, you can change your Alpha level from the screen where you specify variables for analysis. See the main red triangle.
Resources:
