Course Outline

• Why Reliability?
  • A bottom line issue
    • Case study one: impact on the bottom line in the automobile industry
    • Case study two: impact on the bottom line in the electronics industry
    • Case study three: impact on the bottom line in the software industry
    • Case study four: reliability and liability
•  A leader’s perspective on the components of a reliability model process
  • Problem definition
  • Data
  • Model
  • Diagnostics
  • Predictions
  • Decisions
• The leader and the importance of problem definition
  • Spindle example
• What a leader needs to know about data issues
  • Types of data and the corresponding amount of information
    • Space shuttle example
  • Biased Data
    • Lab vs. Field
    • Response Bias and why it matters
    • Omitting data on successes
    • Carburetor story
  • How much data is enough?
    • Two supplier example
  • Three questions to ask before authorizing data collection in the lab or field
• What a leader needs to know about reliability models
  • Why the model matters
    • Early failure example
  • Distinguishing between models by characterizing failure rate behavior
  • Accelerated testing
  • How we get parameters and why it matters
  • What are the right questions to ask
• Essential Diagnostics: How the leader checks reliability models
  • Two plots you should always check
  • Three questions you should always ask
  • Special issues for accelerated testing
• Predictions: Making the model work for the leader
  • What useful information can you get from the model?
    • Warranty times
    • Expected failures
    • Preventive maintenance strategies
    • Identify high pay areas for improvement
    • Optimal replacement strategies
    • Total life cost estimates
    • Acceleration factors
    • Robustness to stresses
  • How accurate are the predictions
    • Fargo example
  • Why the MTBF/MTTF is often a terrible metric
  • Smart comparisons
• Decisions: The key leadership function
  • What are the decision criteria?
  • What are the constraints?
  • Tough calls vs. no-brainers
  • The importance of sensitivity analysis
• The role of leadership
  • Framing the issue of reliability in the organization
    • Bottom line impact
    • Competitive importance
  • Top down emphasis
  • Holding each link in the chain accountable
  • Promoting an organizational culture that fosters reliability
  • The final common sense check