Duration: 5 days CEUs: 3.5 CRP Credits: 5 Course Prerequisites None Assumes Basic Knowledge Of Undergraduate Algebra Elementary Calculus Probability and Statistics Alternative/Similar Course(s) Next Recommended Course D560 or M560 Software Used Primary: Weibull++ Supplemental:ALTA, BlockSim, RGA

Computer Required for Course
Plan to install and explore the course software prior to attending.

Upcoming Seminars:

You may register via the online store, use the print-ready order forms linked from the seminar calendar or contact ReliaSoft.

# G400 - Foundations of Reliability Engineering Data Analysis and Modeling

## Learn Life Data Analysis (aka Weibull Analysis) and Other Essential Reliability Methods

The immensely popular G400 course sets the foundation for all subsequent seminars by introducing and familiarizing the attendee to the fundamental concepts in reliability engineering mathematics, from basic data analysis and modeling to advanced methods and concepts. It begins with an in-depth discussion of the fundamentals of Weibull and Life Data Analysis and continues by expanding the learned concepts to more advanced subjects.

• Understand how life data analysis methodologies can be applied when you need to understand and communicate how a product will perform over time, such as:
• Setting meaningful reliability targets, demonstrating whether an item meets the specification and/or effectively communicating performance estimates to management.
• Identifying whether an item will experience infant mortality and/or wearout and making predictions about performance during the useful life (or warranty) period.
• Evaluating suppliers and/or comparing designs based on reliability.
• Become familiar with the applications of other essential reliability data analysis methods, such as ALT, RBDs and RGA.

Note that G400A is a truncated version of G400 that covers only the first three days.

### Course Outline

Introduction to reliability engineering principles and methods

• Overview of reliability engineering theory and related mathematics, metrics and applications

Fundamentals of life data analysis and applications

• Review of relevant statistical concepts
• Reliability data types and censoring schemes
• Reliability metrics and their interpretation
• In-depth look at the Weibull distribution
• Parameter estimation methods
• Confidence bounds
• Mixed Weibull distribution
• Competing failure modes analysis
• Warranty data analysis
• Model and data set comparisons
• Reliability test design
• Reliability demonstration
• Stress-strength analysis
• Case studies and hands-on practice using Weibull++

Advanced life data modeling and applications

• Combining life-stress relationships with lifetime distributions
• Quantitative accelerated life testing (ALT) data analysis with life-stress models for one or multiple stresses

System analysis, modeling and applications

• Reliability block diagram (RBD) analysis and fault tree analysis
• System reliability equation and metrics
• Importance analysis and reliability allocation methods
• Determining optimum maintenance intervals
• Reliability, availability and maintainability analysis for complex repairable systems

Statistical models for repairable systems and applications

• General renewal process and recurrent event data analysis
• Fielded system analysis and modeling
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