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Accelerated Life Testing Module

Accelerated life testing data, results and stress profiles

 

Accelerated Life Testing module provides all the tools and options you will need for accelerated life testing data analysis. It supports all the data types testing conditions would yield. Data can be entered individually or in groups to accommodate larger datasets.

 

The cumulative damage life-stress model can handle data from tests where the stress varies with time (e.g., a step-stress or ramp-stress profile). You can define and store any number of stress profiles, then easily assign the appropriate profile to each point in an data sheet. Each segment in a profile can be associated with a specific stress value or a time-dependent function. Additionally, it includes Stress Profile Plots for each cumulative damage analysis that shows both the profile and the failures that occurred in each segment.

Accelerated life test planning

 

The module supports the complex mathematical models required to design an effective accelerated life test plan. It offers a choice of one-stress or two-stress test planning methods. Based on your inputs about the expected failure behavior and available test time, it recommends the stress levels to be tested and the most effective allocation of available test units to each level.

 

  • Accelerated non-destructive degradation analysis analyzes degradation data obtained from accelerated non-destructive tests. The result can be used to predict a product’s failure behavior under various use conditions.
  • Accelerated destructive degradation analysis analyzes degradation data obtained from accelerated tests that destroy the specimen or alter its subsequent performance. The result can be used to predict a product’s failure behavior under various use conditions.
  • Life comparisons and stress-strength analysis are designed for statistical comparison of data sets. The Life Comparison allows you to compare two data sets to determine whether items from the first set will outlast those of the second. The Stress-Strength comparison uses the same statistical approach to determine the probability of failure based on the probability of a specified "stress" data set exceeding a specified "strength" data set.
  • Monte Carlo simulation helps you to generate data sets that can be analyzed directly in a standard folio. You can also use the SimuMatic® utility to automatically perform a large number of reliability analyses on data sets that have been created via simulation. These simulated data sets and calculated results can be used to perform a wide variety of reliability tasks.

Integration with nCode GlyphWorks


You have the ability to import and process signals or time series data from nCode GlyphWorks .s3t files and subsequently utilize the post-process profiles in Accelerated Life Testing module (Weibull++) for reliability calculations.

Ready to take your reliability program further?