Life Stress Models - LSM

Life Stress Models (LSM) perform quantitative accelerated life testing data analysis. It also can be used to study the reliability in multiple operational conditions.

 

The results can be used to determine the reliability in target stress (or use stress) using several life-stress relationship, including Arrhenius, Eyring, Inverse Power Law, Temperature-Non Thermal, Temperature-Humidity and General Log-Linear. LSM can analyze up to 8 different stress types.

Contents

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Data Type Entry

Exact Time - Failures
Exact Time - Failures/Suspensions
Exact Time - Grouped/Suspensions
Exact Time - Grouped/Failures/Suspensions

Interval Time - Failures
Interval Time - Failures/Suspensions
Interval Time - Grouped/Suspensions
Interval Time - Grouped/Failures/Suspensions

X (Time) vs Y (Probability of Failure - %)

Life Distribution

Weibull 2 Parameters

Lognormal

Parameter Estimation Methods

MLE

Reliability Plots

Target Stress Probability of Failure vs. Time
Stress Levels Probability of Failure vs. Time 
Reliability vs. Time
Probability of Failure vs. Time
Pdf vs. Time
Failure Rate vs. Time
Life vs. Stress
Acceleration Factor vs. Stress

Reliability Calculations

R(t, stress) - Reliability
F(t, stress) - Probability of Failure
R(T/t, stress) - Conditional Reliability
F(T/t, stress) - Conditional Probability of Failure
BX Life for different stress level
T(R) - Reliable Life for different stress level
Mean Life for different stress level
l(t, stress) - Failure Rate
Parameter Bounds

Confidence Bounds

Methods: Fisher Matrix
Confidence Bounds: Two Sided / Top One-Sided / Bottom-Sided

Other Features

Best Fit - Guide you to choose the best distribution for the dataset
Overlay plots - Multiple items in the same reliability plot
Report - All results and reliability plots in one page
Allow analyze several different items in one analysis
Allow send analysis to other users (R4All and External)