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Reliability. Extending the Quality Concept. ASQ CQA CQE CSSBB CRE APICS CPIM. Director of Product Integrity & Reliability for Stoneridge TED Background in metallurgy & materials science. Kim Pries. What is reliability? Reliability data Probability distributions

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reliability

Reliability

Extending the Quality Concept

kim pries
ASQ

CQA

CQE

CSSBB

CRE

APICS

CPIM

Director of Product Integrity & Reliability for Stoneridge TED

Background in metallurgy & materials science

Kim Pries
summary slide
What is reliability?

Reliability data

Probability distributions

Most common distribution

Weibull mean

Citation

Shapes of Weibull

Scale of Weibull

Location of Weibull

Gamma distribution

Non-parametric data fit

Summary Slide
what is reliability
What is reliability?
  • Reliability is the “quality concept” applied over time
  • Reliability engineering requires a different tool box
reliability data
Reliability data
  • Nearly always “units X to failure,” where units are most often
    • Miles
    • Hours (days, weeks, months)
probability distributions
Probability distributions
  • Exponential
    • “Random failure”
  • Log-normal
  • Weibull
  • Gamma
most common distribution
Most common distribution

Equation

  • Weibull distribution

eta = scale parameter,

beta = shape parameter (or slope),

gamma = location parameter.

weibull mean
Weibull mean
  • Also known as MTBF or MTTF
  • Need to understand gamma function
citation
Citation
  • Using diagrams from Reliasoft Weibull++ 7.x
  • A few from Minitab
summary slide1
Accelerated life testing

Accelerated Life Testing

Highly accelerated life testing

Multi-environment overstress

MEOST, continued

Step-stress

HASS and HASA

Achieving reliability growth

Reliability Growth-Duane Model

Reliability Growth-AMSAA model

Summary Slide
accelerated life testing1
Accelerated Life Testing
  • Can be used to predict life based on testing
  • A typical model looks like
highly accelerated life testing
Highly accelerated life testing
  • No predictive value
  • Reveals weakest portions of design
  • Examples:
    • Thermal shock
    • Special drop testing
    • Mechanical shock
    • Swept sine vibration
multi environment overstress
Derate components

Study thermal behavior

Scan

Finite element analysis

Modular designs

DFM

Mfg line ‘escapes’

RMAs

Robust…high S/N ratio

Design for maintainability

Product liability analysis

Take apart supplier products

FFRs

Multi-environment overstress
meost continued
MEOST, continued
  • Test to failure is goal
  • Combined stress environment
  • Beyond design levels
  • Lower than immediate destruct level
  • Example:
    • Simultaneous
      • Temperature
      • Humidity
      • Vibration
step stress
Step-stress
  • Cumulative damage model
  • Harder to relate to reality
hass and hasa
HASS and HASA
  • Screening versus sampling
  • Small % of life to product
  • Elicit ‘infant mortality’ failures
  • Example:
    • Burn-in
achieving reliability growth
Achieving reliability growth
  • Detect failure causes
  • Feedback
  • Redesign
  • Improved fabrication
  • Verification of redesign
reliability growth amsaa model
Cumulative failures

Initially very poor

Improves over time

Reliability Growth-AMSAA model
summary slide2
Effects of design

Effects of manufacturing

Can’t we predict?

Warranty

Warranty

Serial reliability

Parallel reliability (redundancy)

Other tools

Software reliability

Summary Slide
effects of design
Effects of design
  • Usually the heart of warranty issues
  • Counteract with robust design
effects of manufacturing
Effects of manufacturing
  • Manufacturing can degrade reliability
  • Cannot improve intrinsic design issues
can t we predict
Can’t we predict?
  • MIL-HDBK-217F
    • No parallel circuits
    • Electronics only
    • Extremely conservative
      • Leads to over-engineering
      • Excessive derating
      • Off by factors of at least 2 to 4
warranty
Warranty
  • 1-dimensional
    • Example: miles only
  • 2-dimensional
    • Example:
      • Miles
      • Years
warranty1
Warranty
  • Non-renewing
  • Pro-rated
  • Cumulative
    • Multiple items
  • Reliability improvement
serial reliability
Serial reliability
  • Simple product of the probabilities of failure of components
  • More components = less reliability
parallel reliability redundancy
Parallel reliability (redundancy)
  • Dramatically reduces probability of failure
other tools
Other tools
  • FMEA
  • Fault Tree Analysis
  • Reliability Block Diagrams
    • Simulation
software reliability
Software reliability
  • Difficult to prove
  • Super methods
    • B-method
    • ITU Z.100, Z.105, and Z.120
    • Clean room
summary slide3
Summary Slide
  • What about maintenance?
  • Pogo Pins
  • Pogo Pins (product 1)
  • Pogo Pins (Product 2)
  • Pogo Pin conclusions
  • Preventive vs. Predictive
what about maintenance
What about maintenance?
  • Same math
  • Looking for types of wear and other failure modes
pogo pin conclusions
Pogo Pin conclusions
  • Very quick “infant mortality”
  • Random failure thereafter
  • Difficult to find a nice preventive maintenance schedule
  • Frequent inspection
preventive vs predictive
Preventive vs. Predictive
  • Preventive maintenance
    • Fix before it breaks
    • Statistically based intervals
  • Predictive maintenance
    • Detect anomalies
    • Always uses sensors
the future
The future
  • Combinatorial testing
    • Designed experiments
      • Response surfaces
      • Analysis of variance
      • Analysis of covariance
  • Eyring models
    • Multiple environments