Select Page

# Reliability / Weibull Analysis

The objectives of the Reliability / Weibull Analysis Training:

• Understand reliability concepts and unique aspects of reliability data
• Understand underlying probability and statistical concepts for reliability analysis
• Develop competency in the modeling and analysis of time-to-failure data
• Understand reliability metrics and how to estimate and report them
• Estimate reliability of subsystems and systems
• Determine if reliability specifications are met (at specified confidence level) or whether design improvements are required
• Develop competency in the planning of reliability tests (excluding ALT)
• Analyze existing warranty data to predict future returns
• Develop awareness of more advanced topics in Virtual Reliability Training

## Reliability analysis Seminar Content (3 Days)

1. Reliability Concepts and Reliability Data
• Reliability in Product and Process Development
• Unique Characteristics of Reliability Data
• Censored Data
2. Probability and Statistics Concepts
• Basic Probability Concepts
• Probability Distributions (e.g. Weibull, Lognormal, etc.)
• Probability Distribution Functions
• CDF and Reliability Functions
• Reliability Metrics: Hazard Rate, Mean Time to Failure, Percentiles
• Conditional Reliability
• Burn-In (for Infant Mortality)
3. Assessing & Selecting Models (Distributions) for Failure Data
• Probability Plotting with and without Censored Data
• Identifying the Best Distribution(s)
• Criteria for Comparing Models
4. Estimation of Reliability Characteristics
• Estimation Methods (Maximum Likelihood, Rank Regression)
• Reliability/Online Weibull Analysis Training (and other distributions)
• Precision of Estimates/Confidence Intervals
5. Introduction to Reliability of Systems
• Series Systems
• Parallel Systems
• K-out-of-n Systems
• Complex Systems
• Introduction to System Modeling, Reliability Allocation
6. Introduction to Reliability Test Planning
• Test planning regimes
• Reliability Estimation Test Plans
• Reliability Demonstration Test Plans
• Sample Sizes for Estimation and Demonstration Test Plans
• Sample Size / Testing Time Trade-offs
7. Analysis of Warranty Data
• Data Setup
• Identifying Models for Failure Data
• Forecasting Future Warranty Returns
• Non-Homogeneous Production Periods
8. Introduction to Advanced Topics / Other Topics
• Accelerated Life Testing
• Design for Reliability Training
• Stress/Strength Analysis

# Why is this Course Important?

Achieving high product reliability has become increasingly vital for manufacturers in order to meet customer expectations amid the threat of strong global competition.  Poor reliability can doom a product and jeopardize the reputation of a brand or company.  Inadequate online reliability training courses also presents financial risks from warranty, product recalls, and potential litigation.  When developing new products, it is imperative that manufacturers develop reliability specifications and utilize methods to predict and verify that those reliability specifications will be met.  This presents a difficult challenge in many industries with short product cycles and compressed product development timeframes.  This course provides an in-depth treatment of quantitative methods for predicting and demonstrating product reliability from data gathered from physical testing or from field data.

# Typical Attendees

• Product Engineers
• Design Engineers
• Quality Engineers
• Reliability Engineering Training
• Project / Program Managers
• Manufacturing Personnel
• Six Sigma Professionals
4.6/5 - (65 votes)