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Degradation Analysis - DA

Degradation Analysis module was developed to analyze data and project failures using several mathematical degradation models. This module allows you to perform Life Data Analysis and determine the reliability distribution based on the projected failures generated by the degradation model. It can be applied to different degradation data including crack propagation, deterioration of lubricating oil viscosity, thermography records, wear of brushes, belts and much more. 

Contents

Degradation Models

Linear
Power
Exponential
Logarithmic

DA_01.png
Degradation Plot

Yes

Life Distributions

Weibull 2 Parameters
Weibull 3 Parameters
Mixed Weibull with 2 Populations
Mixed Weibull with 3 Populations
Exponential
Normal
Lognormal

Parameter Estimation Methods

MLE
RRX
RRY

NLR (Mixed Weibull)

Reliability Plots

Probability of Failure vs. Time (distribution paper)
Reliability vs. Time
Probability of Failure vs. Time
Pdf vs. Time
Failure Rate vs. Time
Histogram
Contour Plot
Optimum Replacement Interval Plot

Optimum Inspection Interval Plot

Reliability Calculations

R(t) - Reliability
F(t) - Probability of Failure
R(T/t) - Conditional Reliability
F(T/t) - Conditional Probability of Failure
BX Life
T(R) - Reliable Life
Mean Life
l(t) - Failure Rate
Parameter Bounds
Optimum Replacement Interval

Confidence Bounds

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

Other Features

Degradation Calculator
Best Fit - Guide you to choose the best distribution for the dataset
Report - All DA+LDA results and reliability plots in one page
Allow analyze several different items in one analysis
Allow send analysis to other users (R4All and External)

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