Course Summary

This course will cover basic reliability theory and applications so that the participant will be able to perform standard reliability analyses.

Event Details

16 hours

Instructor-led class training, with opportunities to practice learned skills using prepared data, live demonstrations, and data collected real time in class
Minitab or JMP Statistical Software (Topics may be dependent on the capability of the selected software.)


Weibull analysis models the relationship between product failures and product reliability. These models can be used to predict future performance and to improve product reliability. A practitioner selects a relatively small number of units for test and makes predictions about a population of such units concerning important life characteristics such as the reliability function, mean time to fail or probability of failure at a certain time. The statistical software used allows for easy distribution fitting for reliability data that may be censored and also to build models that describe and predict reliability performance.

Reliability has aspects that touch many aspects of business and industry from product development to process design to equipment design to maintenance to customer data sheets to warranty analysis. This course will cover basic reliability theory and applications so that the participant will be able to perform standard reliability analyses.

The first part of the course introduces basic reliability concepts and terminology, then selected applications are covered. Topics include:

  • Reliability functions
  • Cumulative failure functions
  • Hazard rate functions
  • MTTF, bathtub curve
  • Design life
  • Reporting reliability
  • G and T charts
  • Weibull model and analysis
  • Spare part analysis
  • No/few failures analysis
  • Reliability comparisons
  • PM (Planned Maintenance) frequency
  • Frequency of sampling
  • Reliability demonstration tests for qualifications or verifications
  • Accelerated test methods
  • Reliability life regression

Who Should Attend

This course is designed for managers or engineers who are responsible for reliability growth, reliability performance for either products or processes, equipment designers, supply chain decisions based upon reliability, and maintenance personnel responsible for decreasing downtime and cost.

Learning Objectives

Through training, participants will be able to:

  • Plan and analyze a reliability study using Weibull Analysis
  • Interpret results to supply accurate information to internal and external customers
  • Perform and analyze demonstration tests and accelerated life tests
  • Apply reliability to selected applications including spare part analysis and optimal PM strategies

Course Outline

Introduction to Reliability

  • Questions Reliability Can Answer
  • Probability Models
  • Definition of Reliability
  • Measuring Reliability:  Reliability Function, Cumulative Failure Function, Hazard Function
  • Bathtub Curve
  • MTTF
  • Design Life:  How to Set Goals for Reliability Performance
  • How to quantify Reliability to Report to Management
  • G and T Charts

Weibull Analysis

  • Exponential Model
    • Applications:  Redundancy, Failures on Demand, Spare Parts Analysis
  • Weibull Analysis
    • Weibull Properties
    • Conditional Reliability
    • Censored Data
    • Applications: Reliability Comparisons, Non-Parametric Analysis, Few or No Failures, Design Component Safety Factors

Optimal Time-Based PM Schedules

  • Derivation of Optimal PM Solution
  • Application of the Optimal PM Solution
    • Cost Estimates
    • Flowchart for PM Scheduling
    • PM Interval Weibull Distribution Known
    • PM Interval from Raw Data
    • PM Interval when there are No Failure Data
    • Manual change of PM Interval
    • No Cost Information, PM Set Based Upon Effect and MTTF
    • No Cost Information, PM Set to Control Risk of Downtime

Reliability Testing and Life Regression

  • Reliability Demonstration Tests
    • Basic Concept and Sample Size
  • Accelerated Life Tests
    • Basic Concept and Test Design
    • Acceleration factors
    • Arrhenius Rate Relationship



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