ReliaSoft RGA Fundamentals

ReliaSoft RGA is a powerful engineering software designed to facilitate reliability growth analysis and repairable system analysis. This introductory course equips participants with the essential skills required to effectively utilize RGA for comprehensive reliability growth modeling and analysis. The course offers an in-depth exploration of the RGA interface, ensuring that users can proficiently implement reliability growth methodologies and optimize overhaul times in their professional work

Description

Who Should Attend?

This course is intended as an in introduction to Reliability Growth Analysis with the RGA module in ReliaSoft Weibull++ for new users with little to no experience with the toolset.

The course will cover the core Reliability Growth Analysis and Repairable System Analysis functionality of the tool.

This course does not assume any prior knowledge of the software and covers the fundamental statistical concepts, but a basic understanding of probability theory is beneficial.

Attendees should be familiar with Reliability Engineering Fundamentals and should be able to calculate MTBF values from basic failure data.

Duration

Typically, this online course is split into two three-hour sessions and includes quizzes and practice workshops with the tool. Training courses typically commence at 9:00 and finish by 16:00 (UK time). An optional follow-up Q&A Session is usually scheduled in the following weeks once attendees are bedded in using the software on their own projects.

Agenda

Module 1

  • Welcome and Introductions

  • RGA Terminology and Definitions

  • Calculating Reliability

  • Developmental Testing RGA

  • Fielded System RGA

  • General MTBF Formula (Arithmetic Mean)

  • Relationship Between MTBF and Reliability/Unreliability

  • Calculating Cumulative and Instantaneous MTBF from Failure Data

Module 2

  • RGA data types

  • Reliability calculation for one-shot devices

  • Introduction to Duane Postulate

  • Determining Duane Parameters Using ReliaSoft

  • Crow-AMSAA Model and Its Relation to Duane Postulate

  • Comparison of Duane and Crow-AMSAA Results

  • Failure Mode Classifications in Crow-Extended Model