
Module 4 Estimation of Reliability Metrics
Lesson M04-08
Text: Section 6 pages 26 – 32
Duration: 35 minutes
- Reliability Analysis Methods
- M01 Reliability Concepts & Data
- M02 Probability & Reliability Statistics
- M03 Assessing & Selecting Models for Time-to-Failure Data
- M04 Estimation of Reliability Metrics
- 01 Overview of Reliability Estimation & Methods
- 02 Confidence Intervals & Bounds
- 03 Using Minitab to Estimate Reliability Metrics (Demo)
- 04 Exercise
- 05 Reliability Estimation with Censored Data
- 06 Comparing Multiple Groups
- 07 Exercises
- 08 Handling Multiple Failure Modes & Exercise
- 09 Non-Parametric Estimation
- 10 Other Methods for Reliability Prediction
- M05 Introduction to System Reliability
- M06 Reliability Test Planning
- M07 Analysis of Warranty Data
- M08 Design for Reliability (DFR)
- M09 Introduction to Advanced Topics
Handling Multiple Failure Modes & Exercise
In this lesson, we show a demonstration of modeling multiple failure modes independently and then combining the results to produce overall system level estimates (and graphical output) that account for all failure modes.
Exercise
Data* is available for 30 electronic devices that were installed in typical service environments. Two failure modes have been observed. “Spike” failures were caused by an accumulation of randomly occurring damage from power-line voltage spikes resulting in electronic component failure. “Wear” failures were caused by normal product wear and began to occur after 100,000 cycles of use. The data is found in Dataset_5.MTW.
1. Set up the data and identify distributions that best describe each failure mode (Note: this step may be skipped if desired. For the following steps use: lognormal for “spike” and smallest extreme value for “wear”)
2. Generate the reliability curve for each failure mode separately as well as the reliability curve for the device that includes both failure modes
3. What is the system reliability at 100,000 cycles? What is the 95% lower confidence bound on R(100,000)?
4. Analyze the data without segregating the failure modes. At what times to the model predictions differ the most?
*From Statistical Methods for Reliability Data, Meeker & Escobar p.106
Here are the exercise files mentioned:
- Reliability Analysis Methods
- M01 Reliability Concepts & Data
- M02 Probability & Reliability Statistics
- M03 Assessing & Selecting Models for Time-to-Failure Data
- M04 Estimation of Reliability Metrics
- 01 Overview of Reliability Estimation & Methods
- 02 Confidence Intervals & Bounds
- 03 Using Minitab to Estimate Reliability Metrics (Demo)
- 04 Exercise
- 05 Reliability Estimation with Censored Data
- 06 Comparing Multiple Groups
- 07 Exercises
- 08 Handling Multiple Failure Modes & Exercise
- 09 Non-Parametric Estimation
- 10 Other Methods for Reliability Prediction
- M05 Introduction to System Reliability
- M06 Reliability Test Planning
- M07 Analysis of Warranty Data
- M08 Design for Reliability (DFR)
- M09 Introduction to Advanced Topics
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