Related Analysis Tools
Accelerated Degradation Analysis
The ALTA degradation analysis folio allows you to analyze degradation data obtained under accelerated stress levels in order to estimate when failure would occur under the accelerated conditions. Now the software also automatically performs accelerated life data analysis on the extrapolated failure times and allows you to obtain calculated results and plots for the use stress conditions directly within the same folio — no need to transfer or link to another analysis folio!
Life Comparisons and Stress-Strength Analysis
The software provides two tools designed for statistical comparison of data sets. The Life Comparison tool 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 tool 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.
Both tools have been redesigned and enhanced in the Synthesis version. Now you can save individual analyses in the project for future reference, generate a pdf plot to visualize the comparison and obtain the confidence bounds on the calculated probability, if desired. We have also added a new integrated tool designed to support robust engineering methods by allowing you to solve for design parameters based on target reliability (e.g., determine the strength distribution needed to ensure that strength will exceed stress).
Monte Carlo Simulation
ALTA continues to use Monte Carlo simulation for generating 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, such as:
- Experimenting with the influence of sample sizes and censoring schemes on analysis methods.
- Constructing simulation-based confidence bounds.
- Experimenting with confidence intervals for analyses performed with different distributions.
- Developing and evaluating test plans.