Accendo Reliability

Your Reliability Engineering Professional Development Site

  • Home
  • About
    • Contributors
    • About Us
    • Colophon
    • Survey
  • Reliability.fm
  • 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
      • 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
      • Communicating with FINESSE
      • The RCA
    • 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 Manufacturing Academy
  • eBooks
  • Resources
    • Accendo Authors
    • FMEA Resources
    • Glossary
    • Feed Forward Publications
    • Openings
    • Books
    • Webinar Sources
    • Podcasts
  • Courses
    • Your Courses
    • 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
    • Foundations of RCM online course
    • Reliability Engineering for Heavy Industry
    • How to be an Online Student
    • Quondam Courses
  • Calendar
    • Call for Papers Listing
    • Upcoming Webinars
    • Webinar Calendar
  • Login
    • Member Home
  • Barringer Process Reliability Introduction Course Landing Page
  • Upcoming Live Events
You are here: Home / Articles / Root Cause Knowledge and Models

by Fred Schenkelberg 1 Comment

Root Cause Knowledge and Models

Root Cause Knowledge and Models

Two short questions to evaluate your knowledge of failure mechanisms (root causes) and common reliability models. The answers will be posted in a comment, later.

Which of the following failure root causes is most likely NOT due to power line variation (electronic-based product)?

A. Circuit design margin exceeded
B. Power dissipation
C. In-rush current response
D. Mechanical fatigue

Which theory is customarily used to calculate the effects of temperature on the life of a part?

A. Arrhenius model
B. Duane model
C. Miner’s rule
D. Inverse power rule

And, of course, each question could be reworded in a myriad of ways to explore many failure mechanisms, root causes, and reliability models. Part of the role of a reliability engineer is to have a solid working knowledge of failure mechanisms and how they commonly appear and are caused. Plus, we need a broad working knowledge of the range of models and approaches to understanding the effect of various stresses on failure mechanisms and life estimates.


Related:

Sources of Reliability Data (article)

Common Cause Failures (article)

5 books for a professional reliability engineer (article)

 

Filed Under: Articles, CRE Preparation Notes, Reliability Testing Tagged With: Failure mechanisms, Root Cause Analysis (RCA)

About Fred Schenkelberg

I am the reliability expert at FMS Reliability, a reliability engineering and management consulting firm I founded in 2004. I left Hewlett Packard (HP)’s Reliability Team, where I helped create a culture of reliability across the corporation, to assist other organizations.

« Two Pumps Problem
Dependability »

Comments

  1. Fred Schenkelberg says

    September 30, 2012 at 4:58 PM

    Answers and rationale:

    Which of the following failure root causes is most likely NOT due to power line variation (electronic based product)?

    A. Circuit design margin exceeded
    A traditional failure mechanism due to power line variation
    B. Power dissipation
    A traditional failure mechanism due to power line variation
    C. In-rush current response
    A traditional failure mechanism due to power line variation
    D. Mechanical fatigue
    Correct – while power line fluctuations may cause mechanical and thermal variation within a product leading to mechanical fatigue, it is more likely due to cycling loads or thermal cycling.

    Which theory is customarily used to calculate the effects of temperature on the life of a part?

    A. Arrhenius model
    Correct – especially for the change in chemical reaction rate due to temperature.
    B. Duane model
    Commonly used for modeling reliability growth rates
    C. Miner’s rule
    Commonly used to estimate the fatigue life of a part based upon applied stress cycles.
    D. Inverse power rule
    Commonly used for effects of voltage on dielectric breakdown (and other mechanisms, though not commonly used for thermal stresses.

    Reply

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

CRE Preparation Notes

Article by Fred Schenkelberg

Join Accendo

Join our members-only community for full access to exclusive eBooks, webinars, training, and more.

It’s free and only takes a minute.

Get Full Site Access

Not ready to join?
Stay current on new articles, podcasts, webinars, courses and more added to the Accendo Reliability website each week.
No membership required to subscribe.

[popup type="" link_text="Get Weekly Email Updates" link_class="button" ][display_form id=266][/popup]

  • CRE Preparation Notes
  • CRE Prep
  • Reliability Management
  • Probability and Statistics for Reliability
  • Reliability in Design and Development
  • Reliability Modeling and Predictions
  • Reliability Testing
  • Maintainability and Availability
  • Data Collection and Use

© 2025 FMS Reliability · Privacy Policy · Terms of Service · Cookies Policy