reliability test design linking fatigue and reliability• to demonstrate a reliability target,...

HBM Prenscia: Public

© 2016 HBM

Reliability Test Design: Linking Fatigue and Reliability

Kurt MunsonHBM Prenscia

2016 nCode User Group Meeting

© 2016 HBM October 5-6, 2016 www.ncode.com


© 2016 HBM

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1. Creating durability test specs

2. Introducing reliability to the durability test

What is the Weibull distribution

Reliability and confidence levels

Number of samples to be tested

Duration of test

3. Demonstration of ReliaSoft Weibull++

Agenda




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• Are used to validate a part for product.• Need to be correlated to service loading.• Should prove product durability and reliability.

Lab Durability Tests

Damageservice Damagetest




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4Durability Test Specifications

Test Type Input Loading

Constant amplitude Cyclic, single size, usually uniaxial

Block cycle Cyclic, multiple sizes, usually uniaxial

Time domain Time series, often multiaxial

Frequency domain Random PSD or sine sweep, usually uniaxial




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5Equivalent Damage Test Specification

Measured load

Simplified test load

Damage equivalence:

50,000 cycles @ +/‐850 lb =

4,000 service hours




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Requirements document:‘The part must be free of visible cracks with a reliability greater than 90% with 90% confidence after being subjected to lab loading representative of 4,000 service hours.’

Example Durability Requirement

But what about this 90% reliability and 90% confidence?




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7Deterministic Fatigue

Material Geometry Loads

Fatigue Analysis

Time to Failure




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8Probabilistic Fatigue


PDF

PDF

PDF

Fatigue Analysis

Time to Failure




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• The time‐to‐failure (i.e., life) distribution, can be modelled by a function called PDF (probability density function).

• Typical models/functions used are:• Weibull

• Lognormal

• Normal/Gauss

• Exponential

Probabilistic Fatigue Results


PDF

PDF

PDF

Fatigue Analysis

Time to Failure




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• These models are typically plotted on “Probability Paper,” which linearizes the model and expresses the Probability of Failure (i.e., % Failures) as a function of Operation (time, cycles, etc.).

• The Weibull distribution is frequently utilized, as it’s a flexible model and can describe different failure behaviors (e.g., infant mortality, wear‐out, etc.).

• The “beta” coefficient of the Weibull distribution represents the slope of the probability of failure curve, and it’s also indicative of the failure behavior.

Probability Distributions

Beta= 1




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• To demonstrate a reliability target, enough samples need to be tested, and for a given duration.

• For example, if we would want to demonstrate that at least 90% of our population will survive 1 life (i.e., X cycles), then intuitively, we can test 100 samples for 1 life and determine whether at least 90 survive.

• Can we test less samples?

• How confident are we in the result? Obviously, the more samples we test, the more confident we are.

• Can we test less than 1 life?

• There are available statistical methods to answer these questions.• These methods are available in the “RDT” tool in Weibull++

Reliability Demonstration Testing (RDT)




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• Confidence, sample size and test time are proportionally related:• High confidence = larger sample size or longer test duration.

• We can reduce the number of test samples by testing longer. • Weibull slope beta is used if we want to solve for test duration given a fixed sample

size, or, if our available test duration is other than the target.

Reliability Demonstration Testing

Target

Needed if solving for time, or test duration is other than target life




© 2016 HBM

www.hbmprenscia.com

Kurt Munson

Principal engineering consultant

HBM Prenscia

[email protected]

Thank you!



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