Our World Statistics Day conversations have been a great reminder of how much statistics can inform our lives. Do you have an example of how statistics has made a difference in your life? Share your story with the Community!
Choose Language Hide Translation Bar
Staff (Retired) ltw
Staff (Retired)
Coming in JMP 12: New Destructive Degradation platform

The reliability of components, devices and complex systems is a critical aspect of the quality experience as viewed, and judged, by consumers. Reliability, which is often defined as “Quality over Time,” requires many different analytical techniques depending on the type of data being used and the goal of the findings of interest.

Degradation analysis is one special form of reliability data where a “failure” is defined at some point of deterioration of performance, but not necessarily a hard failure (device no longer works). Hence, these are often referred to as “soft failures.” One common example is the navigation lights on the wing of an aircraft. They may still be operational, but the lumen output has degraded to below a minimum standard. When this occurs, the lamp has been deemed a failure. The lumen output can be “repeatedly measured” over time.

What if the degradation process requires destruction of the unit in order to obtain a measurement? Examples include breaking strength or adhesive performance such as the deterioration of diaper adhesive tape over lengthy storage times. Other examples could be the seal integrity of packaged foods sealed with heat or adhesive bonds. Another aspect is known as disruptive measurements, where devices have to be disassembled for testing and then reassembled, which can affect the reliability. In such cases, only one measurement per unit can be obtained. With increased sample sizes, alternate methods are available to be used: Enter the new Destructive Degradation platform in JMP 12.

The Destructive Degradation platform allows you to fit a model by selecting from a list of 1) a predefined models that include built-in starting values, 2) data distributions and 3) common transformations with improved ease and efficiency.

After selecting the desired model from a pre-built list of models in the “model library” known as the Path Definition, you can visually compare the path style shape examples associated with each model type to the degradation plot to assist in selecting the best model based on the expected behavior. Multiple models may be generated for comparison, altering the underlying distributions and transformations. To determine the best statistical fit, you would then use the model comparison criteria, AICc or BIC.


Once you have generated the models of interest, you can view the Model List section of the report that allows you to easily scroll to any model you generated. You can compare and quickly determine predictions for each model.


A new suite of Prediction Profilers is available so you can perform evaluations and what-if analysis on degradation, crossing times and crossing probabilities. All Profilers include confidence intervals.


Previously, you could perform destructive degradation analysis using the existing JMP Degradation platform (which is still available in JMP 12). However, you needed to supply a JSL formula with starting values. Now, you simply match the shape of possible distribution models to plot: single line, multiple lines, curvature, etc. The new Destructive Degradation platform eliminates all the heavy lifting so you can focus on the analysis. JMP continues to make life simpler for engineers to perform complex statistical analysis with ease to save time in the never-ending process of product improvement.

Article Labels

    There are no labels assigned to this post.