Accendo Reliability

Your Reliability Engineering Professional Development Site

  • Home
  • About
    • Contributors
    • About Us
    • Colophon
    • Survey
  • Reliability.fm
    • Speaking Of Reliability
    • Rooted in Reliability: The Plant Performance Podcast
    • Quality during Design
    • CMMSradio
    • Way of the Quality Warrior
    • Critical Talks
    • Asset Performance
    • Dare to Know
    • Maintenance Disrupted
    • Metal Conversations
    • The Leadership Connection
    • Practical Reliability Podcast
    • Reliability Hero
    • Reliability Matters
    • Reliability it Matters
    • Maintenance Mavericks Podcast
    • Women in Maintenance
    • Accendo Reliability Webinar Series
  • Articles
    • CRE Preparation Notes
    • NoMTBF
    • on Leadership & Career
      • Advanced Engineering Culture
      • ASQR&R
      • Engineering Leadership
      • Managing in the 2000s
      • Product Development and Process Improvement
    • on Maintenance Reliability
      • Aasan Asset Management
      • AI & Predictive Maintenance
      • Asset Management in the Mining Industry
      • CMMS and Maintenance Management
      • CMMS and Reliability
      • Conscious Asset
      • EAM & CMMS
      • Everyday RCM
      • History of Maintenance Management
      • Life Cycle Asset Management
      • Maintenance and Reliability
      • Maintenance Management
      • Plant Maintenance
      • Process Plant Reliability Engineering
      • RCM Blitz®
      • ReliabilityXperience
      • Rob’s Reliability Project
      • The Intelligent Transformer Blog
      • The People Side of Maintenance
      • The Reliability Mindset
    • on Product Reliability
      • Accelerated Reliability
      • Achieving the Benefits of Reliability
      • Apex Ridge
      • Breaking Bad for Reliability
      • Field Reliability Data Analysis
      • Metals Engineering and Product Reliability
      • Musings on Reliability and Maintenance Topics
      • Product Validation
      • Reliability by Design
      • Reliability Competence
      • Reliability Engineering Insights
      • Reliability in Emerging Technology
      • Reliability Knowledge
    • on Risk & Safety
      • CERM® Risk Insights
      • Equipment Risk and Reliability in Downhole Applications
      • Operational Risk Process Safety
    • on Systems Thinking
      • The RCA
      • Communicating with FINESSE
    • on Tools & Techniques
      • Big Data & Analytics
      • Experimental Design for NPD
      • Innovative Thinking in Reliability and Durability
      • Inside and Beyond HALT
      • Inside FMEA
      • Institute of Quality & Reliability
      • Integral Concepts
      • Learning from Failures
      • Progress in Field Reliability?
      • R for Engineering
      • Reliability Engineering Using Python
      • Reliability Reflections
      • Statistical Methods for Failure-Time Data
      • Testing 1 2 3
      • The Hardware Product Develoment Lifecycle
      • The Manufacturing Academy
  • eBooks
  • Resources
    • Special Offers
    • Accendo Authors
    • FMEA Resources
    • Glossary
    • Feed Forward Publications
    • Openings
    • Books
    • Webinar Sources
    • Journals
    • Higher Education
    • Podcasts
  • Courses
    • Your Courses
    • 14 Ways to Acquire Reliability Engineering Knowledge
    • Live Courses
      • Introduction to Reliability Engineering & Accelerated Testings Course Landing Page
      • Advanced Accelerated Testing Course Landing Page
    • Integral Concepts Courses
      • Reliability Analysis Methods Course Landing Page
      • Applied Reliability Analysis Course Landing Page
      • Statistics, Hypothesis Testing, & Regression Modeling Course Landing Page
      • Measurement System Assessment Course Landing Page
      • SPC & Process Capability Course Landing Page
      • Design of Experiments Course Landing Page
    • The Manufacturing Academy Courses
      • An Introduction to Reliability Engineering
      • Reliability Engineering Statistics
      • An Introduction to Quality Engineering
      • Quality Engineering Statistics
      • FMEA in Practice
      • Process Capability Analysis course
      • Root Cause Analysis and the 8D Corrective Action Process course
      • Return on Investment online course
    • Industrial Metallurgist Courses
    • FMEA courses Powered by The Luminous Group
      • FMEA Introduction
      • AIAG & VDA FMEA Methodology
    • Barringer Process Reliability Introduction
      • Barringer Process Reliability Introduction Course Landing Page
    • Fault Tree Analysis (FTA)
    • Foundations of RCM online course
    • Reliability Engineering for Heavy Industry
    • How to be an Online Student
    • Quondam Courses
  • Webinars
    • Upcoming Live Events
    • Accendo Reliability Webinar Series
  • Calendar
    • Call for Papers Listing
    • Upcoming Webinars
    • Webinar Calendar
  • Login
    • Member Home
Home » LMS » Page 29

by Fred Schenkelberg Leave a Comment

V. A. 1. a. Reliability Test Strategies – Types of Testing

V. Reliability Testing
A. Reliability test planning

1. Reliability test strategies (Create)

Create and apply the appropriate test strategies (e.g., truncation, test-to-failure, degradation) for various product development phases.

In this lesson the focus is on the various type of reliability related testing.

 

  • mp4 V. A. 1. a. Reliability Test Strategies - Types of Testing video Download
  • pdf V. A. 1. a. Reliability Test Strategies - Types of Testing slides Download
  • mp3 V. A. 1. a. Reliability Test Strategies - Types of Testing audio Download

Additional References

SOR 070 Creating a Reliability Program Plan that optimizes usage of reliability testing and tools (podcast)

Mechanical Systems Reliability Testing (article

Reliability Testing Considerations (article)

Norris Landberg solder joint fatigue (article)

Quick Quiz

1-2. Identify the kind of failure that would most likely result from insufficient hardware debugging.

(A) early failure
(B) wear-out failure
(C) random failure
(D) catastrophic failure

Answer

(A) early failure

Discussion

The key wording is “most likely” as all types of failure may occur. The best answer in this case corresponds to the type of failures that will most likely occur if the process to find faults or errors is not done well (insufficient hardware debugging).

Since debugging or any product testing typically find faults or errors that are quickly revealed as failure, the most likely issues left undiscovered will also occur soon after the hardware is placed into service, i.e. early failure.

It is possible to conduct insufficient hardware debugging which finds all types of failure except wear-out failure mechanisms. The question does not include information about the details of debugging conducted, just a generic insufficient. Don’t over think the question or potential answers.

Random or catastrophic failures may be detected in hardware testing, plus defects undiscovered may lead to these types of failures. The likelihood of random or catastrophic failures are also more difficult to discover via product testing then the failures that have a decreasing hazard rate (early failures).


1-88. Why must a vendor perform tests on parts?

(A) to estimate total costs
(B) to determine functional capability under specified environmental conditions
(C) to identify the material flow and manufacturing processes to use
(D) to optimize configuration and size

Answer

(B) to determine functional capability under specified environmental conditions

Discussion

Testing is done for many reasons, and from the question there is little information on the nature or pupose of the testing. Yet one thing a vendor has to provide is component/part specificaitons. These are often based on component testing done by the vendor prior to listing performance and environmental conditions on a data sheet.


1-92. Various tests are performed on a new part as specified by a reliability engineer. Which of the following would not be a direct result of those tests?

(A) a disclosure of the part’s deficiencies
(B) data useful to estimate MTBF
(C) knowledge about whether the part meets requirements
(D) an improvement in reliability

Answer

(D) an improvement in reliability

Discussion

Testing does not improve reliability, it only reflects the current state which is useful for the other three options. One could argue that screening out bad units improves field reliability, yet the actual reliability does not really change, we just find and remove failures before they reach customer (or try to as it is a very ineffective process and expensive in most cases)


1-133. A sample for 400 parts is split into two subgroups, each of 200 parts. Testing is performed on each subgroup and each test is stopped after the first failure in that subgroup. A plot is then made of the times to first failure the distribution parameters are estimated. How would you best describe this type of testing?

(A) censored testing
(B) sudden-death testing
(C) step-stress testing
(D) hazard-rate testing

Answer

(B) sudden-death testing

Discussion

The description of the test approach fits the definition of sudden death testing. See the paper by Ryszard Motyka for a comparison of sudden death testing versus traditional censored life testing. http://matwbn.icm.edu.pl/ksiazki/cc/cc36/cc36111.pdf


1-138. In general, why is reliability testing performed?

I.   to monitor reliability growth as a function of time
II.  to meet or exceed customer expectations
III. to detect unanticipated failure modes
IV.  to compare estimated and actual failure rates

 

(A) I and III only
(B) II and IV only
(C) I, II, and III only
(D) I, II, III, and IV

Answer

(D) I, II, III, and IV

Discussion

All valid reasons for reliability testing. In general we conduct testing to learn something about the design of a product or system. We want to reveal problems or check progress toward a goal or to verify design changes are effective. Every reliability test should include a clear statement about the information the test results will provide. Ideally it will also include who needs to make a decision based on the results.

View Previous View Next

by Fred Schenkelberg Leave a Comment

Reliability Testing Planning Introduction

  • mp4 V. A. Reliability Testing Planning Introduction video Download
  • pdf V. A. Reliability Testing Planning Introduction slides Download
  • mp3 V. A. Reliability Testing Planning Introduction audio Download
View Next

by Fred Schenkelberg Leave a Comment

V. A. Reliability Testing Planning

View Previous View Next

by Fred Schenkelberg Leave a Comment

Reliability Testing Introduction

  • mp4 V. Reliability Testing Introduction video Download
  • pdf V. Reliability Testing Introduction slides Download
  • mp3 V. Reliability Testing Introduction audio Download

by Fred Schenkelberg Leave a Comment

V. Reliability Testing

View Previous View Next

by Fred Schenkelberg Leave a Comment

IV. B. 2. c. Reliability Prediction Models – Tolerance Intervals

IV. Reliability Modeling and Prediction
B. Reliability Predictions

2. Reliability prediction methods (Apply)

Use various reliability prediction methods for both repairable and non-repairable components and systems, incorporating test and field reliability data when available.

Don’t confuse tolerance and confidence interval. The former deals with individual values, while the later a parameter (e.g. mean)

 

  • mp4 IV. B. 2. c. Reliability Prediction Models - Tolerance Intervals video Download
  • pdf IV. B. 2. c. Reliability Prediction Models - Tolerance Intervals slides Download
  • mp3 IV. B. 2. c. Reliability Prediction Models - Tolerance Intervals audio Download

Additional References

Tolerance Intervals for Normal Distribution Based Set of Data (article)

Quick Quiz

 

View Previous View Next

by Fred Schenkelberg Leave a Comment

IV. B. 2. b. Reliability Prediction Models – Uncertainty

IV. Reliability Modeling and Prediction
B. Reliability Predictions

2. Reliability prediction methods (Apply)

Use various reliability prediction methods for both repairable and non-repairable components and systems, incorporating test and field reliability data when available.

Even with the best data we are still dealing with a sample taken in the past to estimate the future of component behavior.

 

  • mp4 IV. B. 2. b. Reliability Prediction Models - Uncertainty video Download
  • pdf IV. B. 2. b. Reliability Prediction Models - Uncertainty slides Download
  • mp3 IV. B. 2. b. Reliability Prediction Models - Uncertainty audio Download

Additional References

 

Quick Quiz

 

View Previous View Next

by Fred Schenkelberg Leave a Comment

IV. B. 2. a. Reliability Prediction Models – Considerations

IV. Reliability Modeling and Prediction
B. Reliability Predictions

2. Reliability prediction methods (Apply)

Use various reliability prediction methods for both repairable and non-repairable components and systems, incorporating test and field reliability data when available.

Carefully consider the set of assumption you make when using any prediction method.

 

  • mp4 IV. B. 2. a. Reliability Prediction Models - Considerations video Download
  • pdf IV. B. 2. a. Reliability Prediction Models - Considerations slides Download
  • mp3 IV. B. 2. a. Reliability Prediction Models - Considerations audio Download

Additional References

Reliability Paradigm Shift From Time to Stress Metrics (article)

Creating Meaningful Reliability Predictions (recorded webinar)

When to do a reliability prediction (article)

Consider Reliability Prediction Value (article)

Quick Quiz

1-48. Identify the process that entails defining the system, establishing the reliability model, assigning failure rates to the equipment involved, and computing the reliability for each function and for the system.

(A) defining the program plan
(B) demonstrating reliability
(C) reliability prediction
(D) design review

Answer

C) reliability prediction

Discussion

This could be defining the program plan, if limited to just these activities. Or, it could be the process to create a reliability prediction, which it certainly describes a common approach for predictions.

The process described is not a demonstration as it did not describe any working units or test conditions. We also can rule out a design review, as the process does not include providing feedback on a specific design.


1-61. How would you best characterize reliability prediction?

(A) It is a one-time estimation process.
(B) Is it continuous process starting in the concept and planning stage.
(C) It is more important than reliability attained in the field.
(D) It is finalized with a prediction using a parts-count method.

Answer

(B) Is it continuous process starting in the concept and planning stage.

Discussion

A reliability prediction is an estimate of the future reliability performance of a the system in question. During each stage of the product life-cycle there are estimates of reliability performance including:

  • engineering based guesses,
  • simulations,
  • parts count,
  • parts stress count,
  • vendor data,
  • life testing data,
  • physics of failure modeling,
  • field data analysis.


1-68. If the predicted reliability is higher than the long-term actual probability, what is the most likely cause?

(A) deterioration of manufacturing processes and procedures
(B) poor initial estimation of reliability
(C) lack of employee training
(D) accumulation of random process variations

Answer

(A) deterioration of manufacturing processes and procedures

Discussion

I would say the most likely cause is the huge error associated with reliability predictions. We can rule out the ‘initial estimation’ as while it may be the resulting reliability prediction that is rarely the case for comparison to field performance. Lack of training or accumulation of process variation may increase the difference, yet in this case, given this set of options, the most likely cause is option (A).

 

 

View Previous View Next

by Fred Schenkelberg Leave a Comment

IV. B. 1. Parts Count Predictions and Parts Stress Analysis

IV. Reliability Modeling and Prediction
B. Reliability Predictions

1. Part count prediction and part stress analysis (Apply)

Use parts failure rate data to estimate system- and subsystem-level reliability.

Tally up the failure rates for the individual parts of a system should result in a reasonable estimate of the system reliability Sometimes this may work given good data. An improvement is to consider the component level stress, too.

 

  • mp4 IV. B. 1. Parts Count Predictions and Parts Stress Analysis video Download
  • pdf IV. B. 1. Parts Count Predictions and Parts Stress Analysis slides Download
  • mp3 IV. B. 1. Parts Count Predictions and Parts Stress Analysis audio Download

Additional References

 

Quick Quiz

1-62. During the early design stage, which is the best method to use to predict new device reliability?

(A) part stress analysis
(B) burn-in
(C) parts count
(D) accelerated testing

Answer

(A) part stress analysis

Discussion

Of the options provided only the earliest possible methods, not requiring working prototypes, are the parts count and part stress analysis methods. Part stress analysis attempts to account for the stress experienced by each part providing a little improvement over the part count method.

 

View Previous View Next

by Fred Schenkelberg Leave a Comment

Reliability Predictions Introduction

  • mp4 IV. B. Reliability Predictions Introduction video Download
  • pdf IV. B. Reliability Predictions Introduction slides Download
  • mp3 IV. B. Reliability Predictions Introduction audio Download
View Next

by Fred Schenkelberg Leave a Comment

IV. B. Reliability Predictions

View Previous View Next

by Fred Schenkelberg Leave a Comment

IV. A. 5. Dynamic Reliability

IV. Reliability Modeling and Prediction
A. Reliability Modeling

5. Dynamic reliability (Understand)

Describe dynamic reliability as it relates to failure criteria that change over time or under different conditions.

 

 

  • mp4 IV. A. 5. Dynamic Reliability video Download
  • pdf IV. A. 5. Dynamic Reliability slides Download
  • mp3 IV. A. 5. Dynamic Reliability audio Download

Additional References

 

Quick Quiz

 

View Previous View Next

by Fred Schenkelberg Leave a Comment

IV. A. 4. b. Simulation Techniques – Monte Carlo

IV. Reliability Modeling and Prediction
A. Reliability Modeling

4. Simulation techniques (Apply)

Describe the advantages and limitations of the Monte Carlo and Markov models.

Monte Carlo method uses the variation of elements of a system to assist in the simulation of the system when operating with all that rich variation.

 

  • mp4 IV. A. 4. b. Simulation Techniques - Monte Carlo video Download
  • pdf IV. A. 4. b. Simulation Techniques - Monte Carlo slides Download
  • mp3 IV. A. 4. b. Simulation Techniques - Monte Carlo audio Download

Additional References

Reliability Modeling using Monte Carlo (article)

Reliability and Monte Carlo Determined Tolerances (article)

Quick Quiz

1-32 The Monte Carlo method is a technique that is used to do which of the following?

(A) to insure random sampling from a homogeneous population
(B) to incorporate random chance into the process outcome
(C) to simulate operations when random variations are an essential consideration
(D) to establish quantitative values for unknown restrictive variables

Answer

(C) to simulate operations when random variations are an essential consideration

Discussion

The Monte Carlo method is a computational algorithm that rely on repeated random sampling to obtain numerical results. The results of thousands (or more) random samples are then analyzed to get probabilities of different outcomes.

 

View Previous View Next

by Fred Schenkelberg Leave a Comment

IV. A. 4. a. Simulation Techniques – Markov Models

IV. Reliability Modeling and Prediction
A. Reliability Modeling

4. Simulation techniques (Apply)

Describe the advantages and limitations of the Monte Carlo and Markov models.

Let’s start looking at Markov models, which are great when the elements of a system are not independent (reliability-wise) within the system.

 

  • mp4 IV. A. 4. a. Simulation Techniques - Markov Models video Download
  • pdf IV. A. 4. a. Simulation Techniques - Markov Models slides Download
  • mp3 IV. A. 4. a. Simulation Techniques - Markov Models audio Download

Additional References

 

Quick Quiz

 

View Previous View Next

by Fred Schenkelberg Leave a Comment

IV. A. 3. Physics of Failure Models

IV. Reliability Modeling and Prediction
A. Reliability Modeling

3. Physics of failure models (Apply)

Identify various failure mechanisms (e.g., fracture, corrosion, memory corruption) and select appropriate theoretical models (e.g., Arrhenius, S-N curve) to assess their impact.

Models of stress induced failures take many forms. Each failure mechanisms may have a unique model, which details the relationship between the environmental stresses on a specific structure, material, or combination.

 

  • mp4 IV. A. 3. Physics of Failure Models video Download
  • pdf IV. A. 3. Physics of Failure Models slides Download
  • mp3 IV. A. 3. Physics of Failure Models audio Download

Additional References

 

Quick Quiz

1-40. The linking of exact relationships between variables is a characteristic of which mathematical model?

(A) deterministic process
(B) stochastic process
(C) random process
(D) predictive link

Answer

(A) deterministic process

Discussion

Algorithms, models, procedures, processes, etc. having only one outcome for a given set of inputs are said to be deterministic because their outcome is predetermined.

In probability theory, a stochastic process, or often random process, is a collection of random variables representing the evolution of some system of random values over time. This is the probabilistic counterpart to a deterministic process (or deterministic system).

Predictive link is not a common phrase and may refer to regression analysis or other stochastic relationship.


1-84. Identity all the valid statements about the Arrhenius model.

I.   It is useful for all accelerated testing plans.
II.  It does not rely on temperature.
III. It is useful for significant thermal stresses.
IV.  It provides a relationship of failure to temperature.

(A) I and II only
(B) I and III only
(C) III and IV only
(D) I, III, and IV only

Answer

(C) III and IV only

Discussion

The Arrhenius rate equation and model describes the chemical rate of reaction, and has been used to empirically fit data on occasion independent of understanding the underlying chemical reaction. The primary use of the Arrhenius model it to relate time to failure to temperature and is useful for “significant” thermal stresses which is true if the temperature is not beyond a phase transition for the material involved.


1-107. The time-to-failure distribution to represent a particular reliability situation should be primarily based upon which of the following?

(A) ease of use
(B) convenience
(C) empirical evidence
(D) a representation of the failure mechanism

Answer

(D) a representation of the failure mechanism

Discussion

Understanding and describing the failure mechanisms behavior over time with a distribution permits an accurate model for decision making, test planning, and analysis. When detailed failure mechanism data is not available you may resort to empirical modeling, with the assumption that each failure in the analysis is from the same failure mechanism.

Ease of use and convenience are important considerations and should not overrule the use of the appropriate model to describe the failure mechanism time to failure behavior.

 

View Previous View Next
  • « Previous Page
  • 1
  • …
  • 27
  • 28
  • 29
  • 30
  • 31
  • …
  • 43
  • Next Page »
[hide_from site_member="1" visible_to="public"] Get Weekly Email Updates
[/hide_from]
The Accendo Reliablity logo of a sun face in circuit

[hide_from visible_to='public']Please login to have full access.

[login-form]
[password-recovery-link text='Lost Password? Click here to have it emailed to you.']

Not already a member? It's free and takes only a moment to create an account with your email only.

Join

Your membership brings you all these free resources:

  • Live, monthly reliability webinars & recordings
  • eBooks: Finding Value and Reliability Maturity
  • How To articles & insights
  • Podcasts & additional information within podcast show notes
  • Podcast suggestion box to send us a question or topic for a future episode
  • Course (some with a fee)
  • Largest reliability events calendar
  • Course on a range of topics - coming soon
  • Master reliability classes - coming soon
  • Basic tutorial articles - coming soon
  • With more in the works just for members

[/hide_from][show_to accesslevel="Free" ]
Thanks for being a member [member_first_name]!
[/show_to]

© 2026 FMS Reliability · Privacy Policy · Terms of Service · Cookies Policy

Book the Course with John
  Ask a question or send along a comment. Please login to view and use the contact form.
This site uses cookies to give you a better experience, analyze site traffic, and gain insight to products or offers that may interest you. By continuing, you consent to the use of cookies. Learn how we use cookies, how they work, and how to set your browser preferences by reading our Cookies Policy.