Module 9 Introduction to Advanced Topics

Lesson M09-02

Text: Section 10

Duration: 38 minutes

Introduction to Quantitative ALT

Here we provide a brief introduction into the planning and analysis of quantitative Accelerated Life Tests. The goal is to estimate reliability at normal use conditions based on testing (some) units to failure at a set of higher stress conditions. By developing a model which relates failure times to the stress level(s), we may predict reliability at any stress condition (including the normal use conditions).

We review types of stress loadings and examples of the life/stress relationships as described by various models. An overall approach to analyzing ALT data is suggested and an example is provided.

Module 9 Introduction to Advanced Topics

Lesson M09-03

Text: Section 11

Duration: 12 minutes

Introduction to Repairable System Analysis

A very brief introduction to Repairable Systems Analysis is provided. The concepts of Maintainability and Availability are described.

Module 9 Introduction to Advanced Topics

Lesson M09-04

Text: Section 13, Pages 12 – 18

Duration: 41 minutes

Strength/Stress Analysis

In this lesson, we introduce a method of quantifying risk by calculating failure probabilities based on a characterization of a stress distribution and a strength distribution. A failure occurs when a unit randomly encounters a stress that exceeds its inherent strength. The theory for normally distributed distributions is discussed and an example is worked through. We also discuss the option of using simulation to estimate failure probabilities. This is especially useful when either the stress or strength distribution is not well described by the normal model.

Module 8 Design for Reliability (DFR)

Lesson M08-02

Text: n/a

Duration: 12 minutes

DFR Process & Methodology Overview

Here we review the DFR process and methodology through the proposed phases. Each phase is described along with the common reliability tasks and tools that are typically used in each phase.

Module 8 Design for Reliability (DFR)

Lesson M08-01

Text: n/a

Duration: 11 minutes

Design for Reliability (DFR) Overview

In this lesson we define Design for Reliability and explain why this methodology can efficiently integrate important reliability tasks into the product development process. Next we review some DFR concepts and ideas and look at some of the tools that are typically applied.

Module 7 Analysis of Warranty Data

Lesson M07-04

Text: Section

Duration: 11 minutes

Exercise

The following exercise gives you an opportunity to analyze a set of field data and produce a warranty forecast.

Module 7 Analysis of Warranty Data

Lesson M07-03

Text: Section

Duration: 15 minutes

Minitab Demonstration

Now, we review the Minitab functionality that is available for producing a warranty forecast through a demonstration.

Module 7 Analysis of Warranty Data

Lesson M07-02

Text: Section 13, pages 2 – 11

Duration: 21 minutes

Data Setup & Calculations

Here, we introduce a common way to set up the failure and volumes data for the analysis. Then, we apply conditional failure probabilities to calculate the expected failures for different vintages of units at risk in the field. Finally, we see how by repeating this calculation for different vintages and different forecast periods, we can develop a complete forecast of future returns.

Module 7 Analysis of Warranty Data

Lesson M07-01

Text: Section

Duration: 19 minutes

Warranty Analysis Overview & Key Concepts

In Lesson 1, we discuss uses for Field Data/Warranty analysis and introduce some of the important concepts. We discuss the potential non-homogeneity of field data and how this affects the modeling and forecasting of future field failures.

Module 7 Analysis of Warranty Data

Lesson M07-00

Text: Section 13, pages 2 – 11

Duration: 1 minutes

Introduction to the Analysis of Warranty Data Module

The models developed to analyze time-to-failure data may be used to develop forecasts of the number of failures that may be expected over time.  This is useful for estimating warranty costs, estimating spare part requirements, and reacting to emerging field concerns.  In this module, we learn how to use conditional failure probability to predict the number of failures during the forecast period.

Module 6 Reliability Test Planning

Lesson M06-07

Text:

Duration: 8 minutes

Zero Failure Test Plans Special Case & Module Wrap-up

A special case of the reliability demonstration test plan is covered. This occurs when the testing time is the same time at which we desire to demonstrate reliability. In this instance, fewer assumptions are required, although the plan may not be feasible from a sample size perspective. We end the lesson with a discussion of some practical issues with demonstration testing.

Module 6 Rel6ability Test Planning

Lesson M06-04

Text:

Duration: 8 minutes

Exercise

The exercise to follow allows you to practice specifying demonstration testing plans to achieve the goal of the test.

Module 6 Reliability Test Planning

Lesson M06-05

Text: Section 8, pages 29 – 35

Duration: 30 minutes

Reliability Demonstration Test Planning

Reliability Demonstration tests allow us to show that the reliability requirements have been achieved and this may be done even without actual failures. The types and options in demonstration testing are described. The steps required and a demonstration of an example in Minitab are presented. We also discuss a tool which enables us to consider the chances for failing the test (due to lack of statistical power), even if the population meets the reliability requirements. This may be helpful in selecting the best plan.

Module 6 Reliability Test Planning

Lesson M06-04

Text: Section 8, pages 24 – 28

Duration: 30 minutes

Exercises

This exercise provides an opportunity to practice calculating the sample size necessary to perform a reliability estimation test based on the assumptions provided

Module 6 Reliability Test Planning

Lesson M06-03

Text: Section 8, pages 24 – 28

Duration: 30 minutes

Reliability Estimation Test Planning

Planning should be done before initiating reliability estimation tests.  This ensures that the test is likely to produce estimates with adequate precision to be useful.  Here, we review the steps for planning reliability estimation tests and discuss the factors that will influence the sample size determination.  We walk through an example in Minitab to illustrate the iterative planning process to arrive at approximate sample sizes that will be required.