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AIAG & VDA FMEA Methodology

The AIAG & VDA FMEA Methodology course

Offered by The Luminous Group. Principle instructor Murray Sittsamer.

Course Description

Unlock the power of FMEA with our engaging and interactive eLearning course. Our unique approach, that features learning texts, animations, and the delightful guidance of our kitchen guru, Murray, will demystify the 7-Step Methodology. Watch as we apply these steps to the process of baking delicious chocolate chip cookies, transforming complex concepts into easily digestible knowledge.

For learners with no prior experience with FMEA, our eLearning module “FMEA Introduction” is strongly recommended.

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Get Started with AIAG &VDA FMEA Methodology Today

$50 for 90 day access

Enroll in the FMEA Methodology course

Content Summary

The following content will be highlighted in a go at your own pace on-line learning space.

  • Introduction to FMEA and its importance
  • Overview of the 7-Step Methodology
  • Step 1: Planning – What are we going to accomplish?
  • Step 2: Structure Analysis – What process/product are we examining?
  • Step 3: Function Analysis – What must go right?
  • Step 4: Failure Analysis – What could go wrong?
  • Step 5: Risk Analysis – How do we mitigate potential issues?
  • Step 6: Optimization – How can we improve further?
  • Step 7: Reporting – How do we communicate our findings?
  • Real-world application throughout: Baking chocolate chip cookies

Learning Outcomes

Upon completion of this course, you will:

  • Understand how to model functions, failures, and controls using a timeline.
  • Apply the new AIAG & VDA FMEA 7-Step Methodology.
  • Ensure process steps and inputs are aligned to meet customer requirements.
  • Define Failure Effects, Failure Modes, and Failure Causes.
  • Implement risk mitigation strategies.
  • Optimize your process moving forward based on the FMEA Action Priority

Course Features

  • Holistic, Logical Approach: Demystifies the new FMEA methodology through an engaging digital learning experience.
  • Interactive Content: Includes animations, knowledge checks, and practical examples (like baking cookies) to ensure understanding.
  • Real-World Applications: Transition FMEA from abstract concepts to dynamic, invaluable tools through real-world scenarios.

Course Details

Duration: Self-paced, typically 20 to 30 minutes.

Prerequisites: Completion of “FMEA Introduction” or strong prior experience with Design or Process FMEA.

Pricing: $50 per learner license (Contact us for discounts available for corporate groups.)

Get Started with AIAG & VDA FMEA Methodology Today

Enroll in the FMEA Methodology course

If you have already signed up for the course, login and enjoy.

Lost Password? Click here to have it emailed to you.

About The Luminous Group

The Luminous Group works with Engineering, Manufacturing, and Quality leaders who struggle with:

  • Unexpected or repeat quality issues
  • Reducing costs associated with poor quality
  • Ineffective or inconsistent internal quality audits
  • A lack of leadership, structure, or skills for problem-solving and continuous improvement

Since 1999, we’ve helped hundreds of companies—and thousands of team members—become more empowered, effective, and efficient with enlightening audits, training, and process improvement consulting.

www.LuminousGroup.com

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Measurement System Assessment

M1 Introduction to the Course

A little background and motivation for the material in this course.

  • Welcome
  • Instructor Introduction / Background
  • Course Format / Materials / Software

 

Course Overview

The objective of the curriculum is to provide participants with the analytical tools and methods necessary to:

  • Understand key sources of measurement error
  • Design and Conduct Gage R&R studies to estimate measurement error components (repeatability, reproducibility)
  • Interpret Gage R&R results and identify corrective actions if necessary
  • Plan and Conduct Gage R&R studies for attribute systems
  • Apply control charts to monitor Measurement Systems over time
  • Assess Accuracy and Linearity of Measurement Systems
  • Compare measurement systems to each other with respect to accuracy and precision
  • Handle Non-Replicable Systems (such as Destructive Tests)

The key course features are summarized below:

  • 8 Modules & 36 Lessons
  • Video Presentation of Concepts & Methods
  • Participant Interaction via Pop-Up Questions with Feedback
  • Demonstrations of Analyses using MINITAB Software
  • Interpreting Results/Output
  • Participant Exercises with Presented Solutions
  • Off-line Instructor support available
  • Participant Guide and Supporting Reference Textbook available Electronically and in hard copy

Steven Wachs, Course Instructor

Steven Wachs has 25 years of wide-ranging industry experience in both technical and management positions. Steve has worked as a statistician at Ford Motor Company where he has extensive experience in the development of statistical models, reliability analysis, designed experimentation, and statistical process control.

Steve is currently a Principal Statistician at Integral Concepts, Inc. where he assists manufacturers in the application of statistical methods to reduce variation and improve quality and productivity. He also possesses expertise in the application of reliability methods to achieve robust and reliable products as well as estimate and reduce warranty. Steve regularly speaks at industry conferences and provides workshops in industrial statistical methods worldwide.

 

If you have already signed up for the course, login and enjoy.


Lost Password? Click here to have it emailed to you.

Master Measurement System Assessments starting today.

Your On-demand Course with Instructor Support

Immediate access to all course lessons discussing concepts, reviewing procedures, and flushing out context and applicability.

Plus, I’m here to support you upon request.

Lessons include text, video lectures, quick quizzes, exercises, and activities. The intent is to encourage you to immediately apply the lessons within your organization such that you can start improving your measurement system assessments.

How Long Will the Course Take?

This will depend on how many video lectures you view and how many of the sample exam problems you attempt. The course contains 8 modules, with a total of 36 lessons including 15 exercises. There are approximately 16 hours of lectures.

It is recommended that beyond the lectures, you plan on another 10 to 20 hours for reading and working the exercises. Plus, you are encouraged to ‘try this at work/home’ too.

You can always revisit a lesson or check a detail in the supporting student text.

What are the course prerequisites?

No prior knowledge of statistics or statistical software is required for this course.  Participants should simply be interested in learning how to quantitatively assess the adequacy of measurement systems.

What is your return policy?

If you are not satisfied with the content, send me an email within 30 days for a full refund.

To register for the course today, click the Start Today button and gain immediate access.
Contact us for group pricing and other options.

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Statistics, Hypothesis Testing, & Regression Modeling

Statistics, Hypothesis Testing, & Regression Modeling

Using Mintab software

A little background, motivation, course overview, and a welcome from the instructor, Steven Wachs

The seminar was great, as usual. The books are excellent resources when I am back on the job.

— D.J. Gray Intier Automotive

Get started with the Statistics, Hypothesis Testing, & Regression Modeling course today

This course has 11 modules, 53 lessons, and approximately 36 hours of material, examples, and exercises. Steven is available to answer your questions and discuss course topics. Once purchased, you have full access for six months. The course is on-demand, so you can engage with the course in a way that fits your schedule and interests.

The course format is voice-over slides along with a ‘live’ view of Steven showing how to use Minitab with examples and when reviewing exercise solutions.

The course includes the recorded presentations, a Participant Guide (copies of the slides), Supplemental Textbooks, and the Minitab files that include the datasets for examples and exercises. You can download the guide, textbook, and Mintab files in the third lesson of the Course Introduction module. You may also view the guide and textbook within that lesson online.

The course does include some statistical background and theory, yet the emphasis is on applying statistical methods using Minitab software. We will examine the data setup, analysis, and interpretation over the course of the full course.

Steve Wachs was a wonderful instructor.

Gwen Case, Schrader-Bridgeport Int’l Inc.

Enroll in the Statistics, Hypothesis Testing, & Regression Modeling course.

If you have a team or group ready to enroll in the course, please visit the course purchase options page for details.

If you have already signed up for the course, login and enjoy.

Lost Password? Click here to have it emailed to you.

Training Objectives

The objective of the curriculum is to provide participants with the analytical tools and methods necessary to:

Note: Relevant modules are shown in parentheses.

  • Describe and summarize data effectively with descriptive statistics and graphical methods (1,2)
  • Utilize appropriate probability distributions to describe data (1)
  • Correctly compare groups with respect to means, variability, and proportions by testing hypotheses (e.g. whether the groups have a statistically significant difference) (3,4,5)
  • Estimate key statistics and quantify uncertainty (confidence intervals) (6)
  • Apply Equivalence Testing to determine if groups are the same from a practical perspective (3,4)
  • Characterize expected process variation based on sample data (tolerance intervals) (3)
  • Determine appropriate sample sizes to achieve adequate power for hypothesis tests and equivalence tests (6)
  • Determine appropriate sample sizes for estimation of key statistics (6)
  • Handle discrete data by using common discrete data distributions (7)
  • Conduct Chi-Square tests for relationships between categorical variables (7)
  • Apply Non-Parametric Hypothesis Tests when assumptions for parametric tests are violated (8)
  • Assess whether continuous variables have a significant relationship (correlation) (9)
  • Develop, validate, and utilize predictive models for continuous responses (9,10)
  • Develop and validate Regression Models with Binary, Ordinal, or Nominal responses (11)

Steven Wachs, Course Instructor

Steven Wachs has 25 years of wide-ranging industry experience in both technical and management positions. Steve has worked as a statistician at Ford Motor Company where he has extensive experience in the development of statistical models, reliability analysis, designed experimentation, and statistical process control.

Steve is currently a Principal Statistician at Integral Concepts, Inc. where he assists manufacturers in the application of statistical methods to reduce variation and improve quality and productivity. He also possesses expertise in the application of reliability methods to achieve robust and reliable products as well as estimate and reduce warranty. Steve regularly speaks at industry conferences and provides workshops in industrial statistical methods worldwide.

 

Obvious experience level was great.  Appreciate the real world applications and examples.

former student

Why is This Course Important?

Summarizing Raw Data using relevant and informative statistics is required for effective decision-making. Characterizing continuous data using a good-fitting probability distribution (model) allows us to make inferences from the entire population of data. Graphical Analysis has many uses, including performing exploratory data analysis, effectively summarizing raw data, and presenting and illustrating results that non-statisticians can understand.

Hypothesis Testing is a critical tool in decision-making because it allows us to consider the inherent variation when comparing groups of data to each other or a single group versus a target.  For example: Is the process quality improving over time?  Are two manufacturing lines producing products of equal quality?  Are two suppliers supplying components that have practically equivalent means and variances?  Hypothesis testing allows us to control the risks of making errors when making decisions. Furthermore, selecting appropriate sample size is critical to ensure tests have adequate power so that appropriate conclusions may be drawn.  

Often, data does not meet the necessary assumptions to use traditional (parametric) tests.  In these cases, it’s important that alternate valid methods be utilized (such as nonparametric hypothesis tests).

Predictive models are invaluable for understanding relationships between variables, anticipating outcomes, and optimizing products and processes. Regression Modeling is one important technique for developing predictive models from available data. Handling discrete data is less straightforward than handling continuous data, and different methods must be utilized. This course covers important methods for assessing relationships between categorical variables and developing predictive models with binary, ordinal, and nominal responses.

Typical Attendees

  • Product Engineers
  • Design Engineers
  • Quality Engineers
  • Reliability Engineerings
  • Project / Program Managers
  • Manufacturing Personnel
  • Six Sigma Professionals
  • Scientists
  • R&D Personnel
Enroll in the Statistics, Hypothesis Testing, & Regression Modeling course

If you have a team or group all ready to enroll in the course, please visit the course purchase options page for details.

I have been very pleased with your depth of knowledge and ability to convey that knowledge clearly and quickly.

former student

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ARA Module 11 – Repairable Systems Analysis

ARA Module 11 – Repairable Systems Analysis

of the Applied Reliability Analysis Course

Using Reliasoft Weibull++

So far in this course we have been dealing with non-repairable systems where we model the time to the (first) failure.  Repairable systems analysis is concerned with understanding and modeling the time between failures (over time).  The terminology and models are different than the non-repairable case.  In this module we provide an overview of analysis of repairable systems.  

A little background, motivation, full course overview, and a welcome from the instructor, Steven Wachs

The seminar was great, as usual. The books are excellent resources when I am back on the job.

— D.J. Gray Intier Automotive

Get started with the ARA Module 11 – Repairable Systems Analysis course today

This module-focused course includes the course information section (participants guide, textbook, and example/exercise files), plus the 5 lessons found in module 11. This module may take 2 to 3 hours to complete. Once purchased, you will have 6 months of access to the module’s content.

The full course has 11 modules, 69 lessons, and approximately 32 hours of material, examples, and exercises. Steven is available to answer your questions and discuss course topics. Once purchased, you have full access for six months. The course is on-demand, so you can engage with the course in a way that fits your schedule and interests.

The course format is voice-over slides along with a ‘live’ view of Steven showing how to use Weibull++ with examples and when reviewing exercise solutions.

The course includes the recorded presentations, a Participant Guide (copies of the slides), a Supplemental Textbook, and a Reliasoft file that includes the datasets for examples and exercises. You can download the guide, textbook, and Reliasoft files in the third lesson of the Course Introduction module. You may also view the guide and textbook within that lesson online.

The course does include some statistical background and theory, yet the emphasis is on applying reliability analysis methods using Reliasoft Weibull++. We will examine the data setup, analysis, and interpretation.

Enroll in the Full Applied Reliability Analysis course

Steve Wachs was a wonderful instructor.

Gwen Case, Schrader-Bridgeport Int’l Inc.

Enroll in the ARA Module 11 – Repairable Systems Analysis course

If you have already signed up for the module 1 course, login and enjoy.

Lost Password? Click here to have it emailed to you.

Training Objectives

The key training full course objectives are summarized below (highlighted objectives relate to this module)

  • Understand reliability concepts and unique aspects of reliability data
  • Understand underlying probability and statistical concepts for reliability analysis
  • Develop competency in the modeling and analysis of time-to-failure data
  • Use and interpret probability plots for distribution fitting
  • Understand reliability metrics and how to estimate and report them
  • Handle multiple failure modes in reliability estimation
  • Utilize degradation Data and models to predict failure times for life data analysis
  • Use nonparametric estimation methods when appropriate
  • Determine if reliability specifications are met (at specified confidence level) or whether design improvements are required
  • Estimate estimate uncertainty using confidence intervals and bounds
  • Estimate reliability of subsystems and systems
  • Handle basic series and parallel systems
  • Become aware of system reliability activities such as Reliability Block diagramming, Reliability importance, and Reliability allocation
  • Develop competency in the planning of reliability tests (sample sizes)
  • Use simulation to support estimation test planning
  • Develop reliability demonstration test plans (testing time vs. number of units tradeoffs)
  • Analyze existing warranty data to predict future returns
  • Analyze data from Accelerated Life Tests to estimate reliability at normal use conditions (single stress, multiple stress, time-varying stress models)
  • Plan Accelerated Life tests (sample sizes, determination of test stress combinations, allocation of units to stress levels)
  • Incorporate degradation data modeling into Accelerated Life Test analysis
  • Perform stress-strength analysis using analytical methods, software, and simulation
  • Model reliability from binary response data (i.e. pass/fail)
  • Analyze repair data from repairable systems to predict the number of failures over time, conditional reliability, and failure rates
  • Develop proficiency in the use of Reliasoft Weibull++ for Reliability analyses

Steven Wachs, Course Instructor

Steven Wachs has 25 years of wide-ranging industry experience in both technical and management positions. Steve has worked as a statistician at Ford Motor Company where he has extensive experience in the development of statistical models, reliability analysis, designed experimentation, and statistical process control.

Steve is currently a Principal Statistician at Integral Concepts, Inc. where he assists manufacturers in the application of statistical methods to reduce variation and improve quality and productivity. He also possesses expertise in the application of reliability methods to achieve robust and reliable products as well as estimate and reduce warranty. Steve regularly speaks at industry conferences and provides workshops in industrial statistical methods worldwide.

 

Thorough knowledge of subject matter and ability to communicate it – exceptional instructor.

— Steve Fleishman, Magna Powertrain

Why is This Course Important?

Achieving high product reliability has become increasingly vital for manufacturers in order to meet customer expectations amid the threat of strong global competition.  Poor reliability can doom a product and jeopardize the reputation of a brand or company.  Inadequate online reliability training courses also present financial risks from warranty, product recalls, and potential litigation.  When developing new products, it is imperative that manufacturers develop reliability specifications and utilize methods to predict and verify that those reliability specifications will be met.  This presents a difficult challenge in many industries with short product cycles and compressed product development timeframes.  This course provides an in-depth treatment of quantitative methods for predicting and demonstrating product reliability from data gathered from physical testing or from field data.

Typical Attendees

  • Product Engineers
  • Design Engineers
  • Quality Engineers
  • Reliability Engineering Training
  • Project / Program Managers
  • Manufacturing Personnel
  • Six Sigma Professionals
Enroll in the ARA Module 11 – Repairable Systems Analysis course

Steve is an excellent instructor who is very good on a dry topic. His application ability is great.

Bruce Schubert, BAE Systems

by Leave a Comment

ARA Module 10 – Analysis of Binary Response Data

ARA Module 10 – Analysis of Binary Response Data

of the Applied Reliability Analysis Course

Using Reliasoft Weibull++

This module covers modeling for summarized data resulting from pass/fail (binary) assessments.  That is, the unit either fails or doesn’t fail when exposed to some stress for a specified period of time.  In these problems similar methods are used, but often the probability of survival or failure is estimated as a function of stress level rather than time.  

A little background, motivation, full course overview, and a welcome from the instructor, Steven Wachs

The seminar was great, as usual. The books are excellent resources when I am back on the job.

— D.J. Gray Intier Automotive

Get started with the ARA Module 10 – Analysis of Binary Response Data course today

This module-focused course includes the course information section (participants guide, textbook, and example/exercise files), plus the 3 lessons found in module 10. This module may take 1 to 2 hours to complete. Once purchased, you will have 6 months of access to the module’s content.

The full course has 11 modules, 69 lessons, and approximately 32 hours of material, examples, and exercises. Steven is available to answer your questions and discuss course topics. Once purchased, you have full access for six months. The course is on-demand, so you can engage with the course in a way that fits your schedule and interests.

The course format is voice-over slides along with a ‘live’ view of Steven showing how to use Weibull++ with examples and when reviewing exercise solutions.

The course includes the recorded presentations, a Participant Guide (copies of the slides), a Supplemental Textbook, and a Reliasoft file that includes the datasets for examples and exercises. You can download the guide, textbook, and Reliasoft files in the third lesson of the Course Introduction module. You may also view the guide and textbook within that lesson online.

The course does include some statistical background and theory, yet the emphasis is on applying reliability analysis methods using Reliasoft Weibull++. We will examine the data setup, analysis, and interpretation.

Enroll in the Full Applied Reliability Analysis course

Steve Wachs was a wonderful instructor.

Gwen Case, Schrader-Bridgeport Int’l Inc.

Enroll in the ARA Module 10 – Analysis of Binary Response Data course

If you have already signed up for the module 1 course, login and enjoy.

Lost Password? Click here to have it emailed to you.

Training Objectives

The key training full course objectives are summarized below (highlighted objectives relate to this module)

  • Understand reliability concepts and unique aspects of reliability data
  • Understand underlying probability and statistical concepts for reliability analysis
  • Develop competency in the modeling and analysis of time-to-failure data
  • Use and interpret probability plots for distribution fitting
  • Understand reliability metrics and how to estimate and report them
  • Handle multiple failure modes in reliability estimation
  • Utilize degradation Data and models to predict failure times for life data analysis
  • Use nonparametric estimation methods when appropriate
  • Determine if reliability specifications are met (at specified confidence level) or whether design improvements are required
  • Estimate estimate uncertainty using confidence intervals and bounds
  • Estimate reliability of subsystems and systems
  • Handle basic series and parallel systems
  • Become aware of system reliability activities such as Reliability Block diagramming, Reliability importance, and Reliability allocation
  • Develop competency in the planning of reliability tests (sample sizes)
  • Use simulation to support estimation test planning
  • Develop reliability demonstration test plans (testing time vs. number of units tradeoffs)
  • Analyze existing warranty data to predict future returns
  • Analyze data from Accelerated Life Tests to estimate reliability at normal use conditions (single stress, multiple stress, time-varying stress models)
  • Plan Accelerated Life tests (sample sizes, determination of test stress combinations, allocation of units to stress levels)
  • Incorporate degradation data modeling into Accelerated Life Test analysis
  • Perform stress-strength analysis using analytical methods, software, and simulation
  • Model reliability from binary response data (i.e. pass/fail)
  • Analyze repair data from repairable systems to predict the number of failures over time, conditional reliability, and failure rates
  • Develop proficiency in the use of Reliasoft Weibull++ for Reliability analyses

Steven Wachs, Course Instructor

Steven Wachs has 25 years of wide-ranging industry experience in both technical and management positions. Steve has worked as a statistician at Ford Motor Company where he has extensive experience in the development of statistical models, reliability analysis, designed experimentation, and statistical process control.

Steve is currently a Principal Statistician at Integral Concepts, Inc. where he assists manufacturers in the application of statistical methods to reduce variation and improve quality and productivity. He also possesses expertise in the application of reliability methods to achieve robust and reliable products as well as estimate and reduce warranty. Steve regularly speaks at industry conferences and provides workshops in industrial statistical methods worldwide.

 

Thorough knowledge of subject matter and ability to communicate it – exceptional instructor.

— Steve Fleishman, Magna Powertrain

Why is This Course Important?

Achieving high product reliability has become increasingly vital for manufacturers in order to meet customer expectations amid the threat of strong global competition.  Poor reliability can doom a product and jeopardize the reputation of a brand or company.  Inadequate online reliability training courses also present financial risks from warranty, product recalls, and potential litigation.  When developing new products, it is imperative that manufacturers develop reliability specifications and utilize methods to predict and verify that those reliability specifications will be met.  This presents a difficult challenge in many industries with short product cycles and compressed product development timeframes.  This course provides an in-depth treatment of quantitative methods for predicting and demonstrating product reliability from data gathered from physical testing or from field data.

Typical Attendees

  • Product Engineers
  • Design Engineers
  • Quality Engineers
  • Reliability Engineering Training
  • Project / Program Managers
  • Manufacturing Personnel
  • Six Sigma Professionals
Enroll in the ARA Module 10 – Analysis of Binary Response Data course

Steve is an excellent instructor who is very good on a dry topic. His application ability is great.

Bruce Schubert, BAE Systems

by Leave a Comment

ARA Module 9 – Stress Strength Analysis

ARA Module 9 – Stress Strength Analysis

of the Applied Reliability Analysis Course

Using Reliasoft Weibull++

This module introduces 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 as well as Reliasoft software. This is especially useful when either the stress or strength distribution is not well described by the normal model. 

A little background, motivation, full course overview, and a welcome from the instructor, Steven Wachs

The seminar was great, as usual. The books are excellent resources when I am back on the job.

— D.J. Gray Intier Automotive

Get started with the ARA Module 9- Stress Strength Analysis course today

This module-focused course includes the course information section (participants guide, textbook, and example/exercise files), plus the 4 lessons found in module 9. This module may take 2 to 3 hours to complete. Once purchased, you will have 6 months of access to the module’s content.

The full course has 11 modules, 69 lessons, and approximately 32 hours of material, examples, and exercises. Steven is available to answer your questions and discuss course topics. Once purchased, you have full access for six months. The course is on-demand, so you can engage with the course in a way that fits your schedule and interests.

The course format is voice-over slides along with a ‘live’ view of Steven showing how to use Weibull++ with examples and when reviewing exercise solutions.

The course includes the recorded presentations, a Participant Guide (copies of the slides), a Supplemental Textbook, and a Reliasoft file that includes the datasets for examples and exercises. You can download the guide, textbook, and Reliasoft files in the third lesson of the Course Introduction module. You may also view the guide and textbook within that lesson online.

The course does include some statistical background and theory, yet the emphasis is on applying reliability analysis methods using Reliasoft Weibull++. We will examine the data setup, analysis, and interpretation.

Enroll in the Full Applied Reliability Analysis course

Steve Wachs was a wonderful instructor.

Gwen Case, Schrader-Bridgeport Int’l Inc.

Enroll in the ARA Module 9 – Stress Strength Analysis course

If you have already signed up for the module 1 course, login and enjoy.

Lost Password? Click here to have it emailed to you.

Training Objectives

The key training full course objectives are summarized below (highlighted objectives relate to this module)

  • Understand reliability concepts and unique aspects of reliability data
  • Understand underlying probability and statistical concepts for reliability analysis
  • Develop competency in the modeling and analysis of time-to-failure data
  • Use and interpret probability plots for distribution fitting
  • Understand reliability metrics and how to estimate and report them
  • Handle multiple failure modes in reliability estimation
  • Utilize degradation Data and models to predict failure times for life data analysis
  • Use nonparametric estimation methods when appropriate
  • Determine if reliability specifications are met (at specified confidence level) or whether design improvements are required
  • Estimate estimate uncertainty using confidence intervals and bounds
  • Estimate reliability of subsystems and systems
  • Handle basic series and parallel systems
  • Become aware of system reliability activities such as Reliability Block diagramming, Reliability importance, and Reliability allocation
  • Develop competency in the planning of reliability tests (sample sizes)
  • Use simulation to support estimation test planning
  • Develop reliability demonstration test plans (testing time vs. number of units tradeoffs)
  • Analyze existing warranty data to predict future returns
  • Analyze data from Accelerated Life Tests to estimate reliability at normal use conditions (single stress, multiple stress, time-varying stress models)
  • Plan Accelerated Life tests (sample sizes, determination of test stress combinations, allocation of units to stress levels)
  • Incorporate degradation data modeling into Accelerated Life Test analysis
  • Perform stress-strength analysis using analytical methods, software, and simulation
  • Model reliability from binary response data (i.e. pass/fail)
  • Analyze repair data from repairable systems to predict the number of failures over time, conditional reliability, and failure rates
  • Develop proficiency in the use of Reliasoft Weibull++ for Reliability analyses

Steven Wachs, Course Instructor

Steven Wachs has 25 years of wide-ranging industry experience in both technical and management positions. Steve has worked as a statistician at Ford Motor Company where he has extensive experience in the development of statistical models, reliability analysis, designed experimentation, and statistical process control.

Steve is currently a Principal Statistician at Integral Concepts, Inc. where he assists manufacturers in the application of statistical methods to reduce variation and improve quality and productivity. He also possesses expertise in the application of reliability methods to achieve robust and reliable products as well as estimate and reduce warranty. Steve regularly speaks at industry conferences and provides workshops in industrial statistical methods worldwide.

 

Thorough knowledge of subject matter and ability to communicate it – exceptional instructor.

— Steve Fleishman, Magna Powertrain

Why is This Course Important?

Achieving high product reliability has become increasingly vital for manufacturers in order to meet customer expectations amid the threat of strong global competition.  Poor reliability can doom a product and jeopardize the reputation of a brand or company.  Inadequate online reliability training courses also present financial risks from warranty, product recalls, and potential litigation.  When developing new products, it is imperative that manufacturers develop reliability specifications and utilize methods to predict and verify that those reliability specifications will be met.  This presents a difficult challenge in many industries with short product cycles and compressed product development timeframes.  This course provides an in-depth treatment of quantitative methods for predicting and demonstrating product reliability from data gathered from physical testing or from field data.

Typical Attendees

  • Product Engineers
  • Design Engineers
  • Quality Engineers
  • Reliability Engineering Training
  • Project / Program Managers
  • Manufacturing Personnel
  • Six Sigma Professionals
Enroll in the ARA Module 9 – Stress Strength Analysis course

Steve is an excellent instructor who is very good on a dry topic. His application ability is great.

Bruce Schubert, BAE Systems

by Leave a Comment

ARA Module 8 – Accelerated Life Testing

ARA Module 8 – Accelerated Life Testing

of the Applied Reliability Analysis Course

Using Reliasoft Weibull++

This module covers the planning and analysis of Accelerated Life Tests (ALT).  ALT is a useful methodology for obtaining failure information in less time than it takes for tests performed at normal use conditions.  Quantitative ALTs allow the estimation of reliability statistics at normal use conditions based on failures observes at various stress conditions.  While more complex than regular reliability tests, they can yield useful information is significantly less time.

A little background, motivation, full course overview, and a welcome from the instructor, Steven Wachs

The seminar was great, as usual. The books are excellent resources when I am back on the job.

— D.J. Gray Intier Automotive

Get started with the ARA Module 8 – Accelerated Life Testing course today

This module-focused course includes the course information section (participants guide, textbook, and example/exercise files), plus the 9 lessons found in module 8. This module may take 6 to 7 hours to complete. Once purchased, you will have 6 months of access to the module’s content.

The full course has 11 modules, 69 lessons, and approximately 32 hours of material, examples, and exercises. Steven is available to answer your questions and discuss course topics. Once purchased, you have full access for six months. The course is on-demand, so you can engage with the course in a way that fits your schedule and interests.

The course format is voice-over slides along with a ‘live’ view of Steven showing how to use Weibull++ with examples and when reviewing exercise solutions.

The course includes the recorded presentations, a Participant Guide (copies of the slides), a Supplemental Textbook, and a Reliasoft file that includes the datasets for examples and exercises. You can download the guide, textbook, and Reliasoft files in the third lesson of the Course Introduction module. You may also view the guide and textbook within that lesson online.

The course does include some statistical background and theory, yet the emphasis is on applying reliability analysis methods using Reliasoft Weibull++. We will examine the data setup, analysis, and interpretation.

Enroll in the Full Applied Reliability Analysis course

Steve Wachs was a wonderful instructor.

Gwen Case, Schrader-Bridgeport Int’l Inc.

Enroll in the ARA Module 8 – Accelerated Life Testing course

If you have already signed up for the module 1 course, login and enjoy.

Lost Password? Click here to have it emailed to you.

Training Objectives

The key training full course objectives are summarized below (highlighted objectives relate to this module)

  • Understand reliability concepts and unique aspects of reliability data
  • Understand underlying probability and statistical concepts for reliability analysis
  • Develop competency in the modeling and analysis of time-to-failure data
  • Use and interpret probability plots for distribution fitting
  • Understand reliability metrics and how to estimate and report them
  • Handle multiple failure modes in reliability estimation
  • Utilize degradation Data and models to predict failure times for life data analysis
  • Use nonparametric estimation methods when appropriate
  • Determine if reliability specifications are met (at specified confidence level) or whether design improvements are required
  • Estimate estimate uncertainty using confidence intervals and bounds
  • Estimate reliability of subsystems and systems
  • Handle basic series and parallel systems
  • Become aware of system reliability activities such as Reliability Block diagramming, Reliability importance, and Reliability allocation
  • Develop competency in the planning of reliability tests (sample sizes)
  • Use simulation to support estimation test planning
  • Develop reliability demonstration test plans (testing time vs. number of units tradeoffs)
  • Analyze existing warranty data to predict future returns
  • Analyze data from Accelerated Life Tests to estimate reliability at normal use conditions (single stress, multiple stress, time-varying stress models)
  • Plan Accelerated Life tests (sample sizes, determination of test stress combinations, allocation of units to stress levels)
  • Incorporate degradation data modeling into Accelerated Life Test analysis
  • Perform stress-strength analysis using analytical methods, software, and simulation
  • Model reliability from binary response data (i.e. pass/fail)
  • Analyze repair data from repairable systems to predict the number of failures over time, conditional reliability, and failure rates
  • Develop proficiency in the use of Reliasoft Weibull++ for Reliability analyses

Steven Wachs, Course Instructor

Steven Wachs has 25 years of wide-ranging industry experience in both technical and management positions. Steve has worked as a statistician at Ford Motor Company where he has extensive experience in the development of statistical models, reliability analysis, designed experimentation, and statistical process control.

Steve is currently a Principal Statistician at Integral Concepts, Inc. where he assists manufacturers in the application of statistical methods to reduce variation and improve quality and productivity. He also possesses expertise in the application of reliability methods to achieve robust and reliable products as well as estimate and reduce warranty. Steve regularly speaks at industry conferences and provides workshops in industrial statistical methods worldwide.

 

Thorough knowledge of subject matter and ability to communicate it – exceptional instructor.

— Steve Fleishman, Magna Powertrain

Why is This Course Important?

Achieving high product reliability has become increasingly vital for manufacturers in order to meet customer expectations amid the threat of strong global competition.  Poor reliability can doom a product and jeopardize the reputation of a brand or company.  Inadequate online reliability training courses also present financial risks from warranty, product recalls, and potential litigation.  When developing new products, it is imperative that manufacturers develop reliability specifications and utilize methods to predict and verify that those reliability specifications will be met.  This presents a difficult challenge in many industries with short product cycles and compressed product development timeframes.  This course provides an in-depth treatment of quantitative methods for predicting and demonstrating product reliability from data gathered from physical testing or from field data.

Typical Attendees

  • Product Engineers
  • Design Engineers
  • Quality Engineers
  • Reliability Engineering Training
  • Project / Program Managers
  • Manufacturing Personnel
  • Six Sigma Professionals
Enroll in the ARA Module 8 – Accelerated Life Testing course

Steve is an excellent instructor who is very good on a dry topic. His application ability is great.

Bruce Schubert, BAE Systems

by Leave a Comment

ARA Module 7 – Reliability Test Planning

ARA Module 7 – Reliability Test Planning

of the Applied Reliability Analysis Course

Using Reliasoft Weibull++

Reliability testing is a key component for ensuring that Reliability targets are achieved.  Planning for reliability tests is important to ensure that the results are likely to be useful.  In this module, we look at planning for both reliability estimation tests and reliability demonstration tests.  Essentially, we must test enough units for long enough to be able to adequately estimate reliability or demonstrate that targets are met.

A little background, motivation, full course overview, and a welcome from the instructor, Steven Wachs

The seminar was great, as usual. The books are excellent resources when I am back on the job.

— D.J. Gray Intier Automotive

Get started with the ARA Module 7 – Reliability Test Planning course today

This module-focused course includes the course information section (participants guide, textbook, and example/exercise files), plus the 7 lessons found in module 7. This module may take 3 to 4 hours to complete. Once purchased, you will have 6 months of access to the module’s content.

The full course has 11 modules, 69 lessons, and approximately 32 hours of material, examples, and exercises. Steven is available to answer your questions and discuss course topics. Once purchased, you have full access for six months. The course is on-demand, so you can engage with the course in a way that fits your schedule and interests.

The course format is voice-over slides along with a ‘live’ view of Steven showing how to use Weibull++ with examples and when reviewing exercise solutions.

The course includes the recorded presentations, a Participant Guide (copies of the slides), a Supplemental Textbook, and a Reliasoft file that includes the datasets for examples and exercises. You can download the guide, textbook, and Reliasoft files in the third lesson of the Course Introduction module. You may also view the guide and textbook within that lesson online.

The course does include some statistical background and theory, yet the emphasis is on applying reliability analysis methods using Reliasoft Weibull++. We will examine the data setup, analysis, and interpretation.

Enroll in the Full Applied Reliability Analysis course

Steve Wachs was a wonderful instructor.

Gwen Case, Schrader-Bridgeport Int’l Inc.

Enroll in the ARA Module 7 – Reliability Test Planning course

If you have already signed up for the module 1 course, login and enjoy.

Lost Password? Click here to have it emailed to you.

Training Objectives

The key training full course objectives are summarized below (highlighted objectives relate to this module)

  • Understand reliability concepts and unique aspects of reliability data
  • Understand underlying probability and statistical concepts for reliability analysis
  • Develop competency in the modeling and analysis of time-to-failure data
  • Use and interpret probability plots for distribution fitting
  • Understand reliability metrics and how to estimate and report them
  • Handle multiple failure modes in reliability estimation
  • Utilize degradation Data and models to predict failure times for life data analysis
  • Use nonparametric estimation methods when appropriate
  • Determine if reliability specifications are met (at specified confidence level) or whether design improvements are required
  • Estimate estimate uncertainty using confidence intervals and bounds
  • Estimate reliability of subsystems and systems
  • Handle basic series and parallel systems
  • Become aware of system reliability activities such as Reliability Block diagramming, Reliability importance, and Reliability allocation
  • Develop competency in the planning of reliability tests (sample sizes)
  • Use simulation to support estimation test planning
  • Develop reliability demonstration test plans (testing time vs. number of units tradeoffs)
  • Analyze existing warranty data to predict future returns
  • Analyze data from Accelerated Life Tests to estimate reliability at normal use conditions (single stress, multiple stress, time-varying stress models)
  • Plan Accelerated Life tests (sample sizes, determination of test stress combinations, allocation of units to stress levels)
  • Incorporate degradation data modeling into Accelerated Life Test analysis
  • Perform stress-strength analysis using analytical methods, software, and simulation
  • Model reliability from binary response data (i.e. pass/fail)
  • Analyze repair data from repairable systems to predict the number of failures over time, conditional reliability, and failure rates
  • Develop proficiency in the use of Reliasoft Weibull++ for Reliability analyses

Steven Wachs, Course Instructor

Steven Wachs has 25 years of wide-ranging industry experience in both technical and management positions. Steve has worked as a statistician at Ford Motor Company where he has extensive experience in the development of statistical models, reliability analysis, designed experimentation, and statistical process control.

Steve is currently a Principal Statistician at Integral Concepts, Inc. where he assists manufacturers in the application of statistical methods to reduce variation and improve quality and productivity. He also possesses expertise in the application of reliability methods to achieve robust and reliable products as well as estimate and reduce warranty. Steve regularly speaks at industry conferences and provides workshops in industrial statistical methods worldwide.

 

Thorough knowledge of subject matter and ability to communicate it – exceptional instructor.

— Steve Fleishman, Magna Powertrain

Why is This Course Important?

Achieving high product reliability has become increasingly vital for manufacturers in order to meet customer expectations amid the threat of strong global competition.  Poor reliability can doom a product and jeopardize the reputation of a brand or company.  Inadequate online reliability training courses also present financial risks from warranty, product recalls, and potential litigation.  When developing new products, it is imperative that manufacturers develop reliability specifications and utilize methods to predict and verify that those reliability specifications will be met.  This presents a difficult challenge in many industries with short product cycles and compressed product development timeframes.  This course provides an in-depth treatment of quantitative methods for predicting and demonstrating product reliability from data gathered from physical testing or from field data.

Typical Attendees

  • Product Engineers
  • Design Engineers
  • Quality Engineers
  • Reliability Engineering Training
  • Project / Program Managers
  • Manufacturing Personnel
  • Six Sigma Professionals
Enroll in the ARA Module 7 – Reliability Test Planning course

Steve is an excellent instructor who is very good on a dry topic. His application ability is great.

Bruce Schubert, BAE Systems

by Leave a Comment

ARA Module 6 – Analysis of Field Data — Warranty Forecasting

ARA Module 6 – Analysis of Field Data — Warranty Forecasting

of the Applied Reliability Analysis Course

Using Reliasoft Weibull++

In this introductory module, we define Reliability and cover many important reliability concepts.  We discuss why reliability performance is so important and the types of questions that may be answered by analyzing failure data.  Different types of reliability data are reviewed.  We introduce the concept of censored data which allows us to correctly utilize partial or incomplete data in the analysis of test or field data.  We cover the Bathtub Curve which illustrates the types of failures that may occur over a product’s lifetime.  Finally, we introduce the reliability function and discuss product reliability goals.

A little background, motivation, full course overview, and a welcome from the instructor, Steven Wachs

The seminar was great, as usual. The books are excellent resources when I am back on the job.

— D.J. Gray Intier Automotive

Get started with the ARA Module 6 – Analysis of Field Data – Warranty Forecastin course today

This module-focused course includes the course information section (participants guide, textbook, and example/exercise files), plus the 4 lessons found in module 6. This module may take 2 to 3 hours to complete. Once purchased, you will have 6 months of access to the module’s content.

The full course has 11 modules, 69 lessons, and approximately 32 hours of material, examples, and exercises. Steven is available to answer your questions and discuss course topics. Once purchased, you have full access for six months. The course is on-demand, so you can engage with the course in a way that fits your schedule and interests.

The course format is voice-over slides along with a ‘live’ view of Steven showing how to use Weibull++ with examples and when reviewing exercise solutions.

The course includes the recorded presentations, a Participant Guide (copies of the slides), a Supplemental Textbook, and a Reliasoft file that includes the datasets for examples and exercises. You can download the guide, textbook, and Reliasoft files in the third lesson of the Course Introduction module. You may also view the guide and textbook within that lesson online.

The course does include some statistical background and theory, yet the emphasis is on applying reliability analysis methods using Reliasoft Weibull++. We will examine the data setup, analysis, and interpretation.

Enroll in the Full Applied Reliability Analysis course

Steve Wachs was a wonderful instructor.

Gwen Case, Schrader-Bridgeport Int’l Inc.

Enroll in the ARA Module 6 – Analysis of Field Data – Warranty Forecasting course

If you have already signed up for the module 1 course, login and enjoy.

Lost Password? Click here to have it emailed to you.

Training Objectives

The key training full course objectives are summarized below (highlighted objectives relate to this module)

  • Understand reliability concepts and unique aspects of reliability data
  • Understand underlying probability and statistical concepts for reliability analysis
  • Develop competency in the modeling and analysis of time-to-failure data
  • Use and interpret probability plots for distribution fitting
  • Understand reliability metrics and how to estimate and report them
  • Handle multiple failure modes in reliability estimation
  • Utilize degradation Data and models to predict failure times for life data analysis
  • Use nonparametric estimation methods when appropriate
  • Determine if reliability specifications are met (at specified confidence level) or whether design improvements are required
  • Estimate estimate uncertainty using confidence intervals and bounds
  • Estimate reliability of subsystems and systems
  • Handle basic series and parallel systems
  • Become aware of system reliability activities such as Reliability Block diagramming, Reliability importance, and Reliability allocation
  • Develop competency in the planning of reliability tests (sample sizes)
  • Use simulation to support estimation test planning
  • Develop reliability demonstration test plans (testing time vs. number of units tradeoffs)
  • Analyze existing warranty data to predict future returns
  • Analyze data from Accelerated Life Tests to estimate reliability at normal use conditions (single stress, multiple stress, time-varying stress models)
  • Plan Accelerated Life tests (sample sizes, determination of test stress combinations, allocation of units to stress levels)
  • Incorporate degradation data modeling into Accelerated Life Test analysis
  • Perform stress-strength analysis using analytical methods, software, and simulation
  • Model reliability from binary response data (i.e. pass/fail)
  • Analyze repair data from repairable systems to predict the number of failures over time, conditional reliability, and failure rates
  • Develop proficiency in the use of Reliasoft Weibull++ for Reliability analyses

Steven Wachs, Course Instructor

Steven Wachs has 25 years of wide-ranging industry experience in both technical and management positions. Steve has worked as a statistician at Ford Motor Company where he has extensive experience in the development of statistical models, reliability analysis, designed experimentation, and statistical process control.

Steve is currently a Principal Statistician at Integral Concepts, Inc. where he assists manufacturers in the application of statistical methods to reduce variation and improve quality and productivity. He also possesses expertise in the application of reliability methods to achieve robust and reliable products as well as estimate and reduce warranty. Steve regularly speaks at industry conferences and provides workshops in industrial statistical methods worldwide.

 

Thorough knowledge of subject matter and ability to communicate it – exceptional instructor.

— Steve Fleishman, Magna Powertrain

Why is This Course Important?

Achieving high product reliability has become increasingly vital for manufacturers in order to meet customer expectations amid the threat of strong global competition.  Poor reliability can doom a product and jeopardize the reputation of a brand or company.  Inadequate online reliability training courses also present financial risks from warranty, product recalls, and potential litigation.  When developing new products, it is imperative that manufacturers develop reliability specifications and utilize methods to predict and verify that those reliability specifications will be met.  This presents a difficult challenge in many industries with short product cycles and compressed product development timeframes.  This course provides an in-depth treatment of quantitative methods for predicting and demonstrating product reliability from data gathered from physical testing or from field data.

Typical Attendees

  • Product Engineers
  • Design Engineers
  • Quality Engineers
  • Reliability Engineering Training
  • Project / Program Managers
  • Manufacturing Personnel
  • Six Sigma Professionals
Enroll in the ARA Module 6 – Analysis of Field Data – Warranty Forecasting course

Steve is an excellent instructor who is very good on a dry topic. His application ability is great.

Bruce Schubert, BAE Systems

by Leave a Comment

ARA Module 5 – Introduction to Reliability of Systems

ARA Module 5 – Introduction to Reliability of Systems

of the Applied Reliability Analysis Course

Using Reliasoft Weibull++

In Module 5, we extend the estimation of component reliability to the reliability estimation of a systemcomprised of multiple components.  The system reliability depends both on the component reliabilities as well as their configuration.  Redundant components allow the system reliability to achieve levels that exceed the component reliabilities.  We explore the basic series and parallel structures as well as k-out-of-n parallel systems.  We also introduce more complex systems and various aspects of system reliability including reliability importance and reliability allocation. 

A little background, motivation, full course overview, and a welcome from the instructor, Steven Wachs

The seminar was great, as usual. The books are excellent resources when I am back on the job.

— D.J. Gray Intier Automotive

Get started with the ARA Module 5 – Introduction to Reliability of Systems course today

This module-focused course includes the course information section (participants guide, textbook, and example/exercise files), plus the 6 lessons found in module 5. This module may take 3 to 4 hours to complete. Once purchased, you will have 6 months of access to the module’s content.

The full course has 11 modules, 69 lessons, and approximately 32 hours of material, examples, and exercises. Steven is available to answer your questions and discuss course topics. Once purchased, you have full access for six months. The course is on-demand, so you can engage with the course in a way that fits your schedule and interests.

The course format is voice-over slides along with a ‘live’ view of Steven showing how to use Weibull++ with examples and when reviewing exercise solutions.

The course includes the recorded presentations, a Participant Guide (copies of the slides), a Supplemental Textbook, and a Reliasoft file that includes the datasets for examples and exercises. You can download the guide, textbook, and Reliasoft files in the third lesson of the Course Introduction module. You may also view the guide and textbook within that lesson online.

The course does include some statistical background and theory, yet the emphasis is on applying reliability analysis methods using Reliasoft Weibull++. We will examine the data setup, analysis, and interpretation.

Enroll in the Full Applied Reliability Analysis course

Steve Wachs was a wonderful instructor.

Gwen Case, Schrader-Bridgeport Int’l Inc.

Enroll in the ARA Module 5 Introduction to Reliability of Systems course

If you have already signed up for the module 1 course, login and enjoy.

Lost Password? Click here to have it emailed to you.

Training Objectives

The key training full course objectives are summarized below (highlighted objectives relate to this module)

  • Understand reliability concepts and unique aspects of reliability data
  • Understand underlying probability and statistical concepts for reliability analysis
  • Develop competency in the modeling and analysis of time-to-failure data
  • Use and interpret probability plots for distribution fitting
  • Understand reliability metrics and how to estimate and report them
  • Handle multiple failure modes in reliability estimation
  • Utilize degradation Data and models to predict failure times for life data analysis
  • Use nonparametric estimation methods when appropriate
  • Determine if reliability specifications are met (at specified confidence level) or whether design improvements are required
  • Estimate estimate uncertainty using confidence intervals and bounds
  • Estimate reliability of subsystems and systems
  • Handle basic series and parallel systems
  • Become aware of system reliability activities such as Reliability Block diagramming, Reliability importance, and Reliability allocation
  • Develop competency in the planning of reliability tests (sample sizes)
  • Use simulation to support estimation test planning
  • Develop reliability demonstration test plans (testing time vs. number of units tradeoffs)
  • Analyze existing warranty data to predict future returns
  • Analyze data from Accelerated Life Tests to estimate reliability at normal use conditions (single stress, multiple stress, time-varying stress models)
  • Plan Accelerated Life tests (sample sizes, determination of test stress combinations, allocation of units to stress levels)
  • Incorporate degradation data modeling into Accelerated Life Test analysis
  • Perform stress-strength analysis using analytical methods, software, and simulation
  • Model reliability from binary response data (i.e. pass/fail)
  • Analyze repair data from repairable systems to predict the number of failures over time, conditional reliability, and failure rates
  • Develop proficiency in the use of Reliasoft Weibull++ for Reliability analyses

Steven Wachs, Course Instructor

Steven Wachs has 25 years of wide-ranging industry experience in both technical and management positions. Steve has worked as a statistician at Ford Motor Company where he has extensive experience in the development of statistical models, reliability analysis, designed experimentation, and statistical process control.

Steve is currently a Principal Statistician at Integral Concepts, Inc. where he assists manufacturers in the application of statistical methods to reduce variation and improve quality and productivity. He also possesses expertise in the application of reliability methods to achieve robust and reliable products as well as estimate and reduce warranty. Steve regularly speaks at industry conferences and provides workshops in industrial statistical methods worldwide.

 

Thorough knowledge of subject matter and ability to communicate it – exceptional instructor.

— Steve Fleishman, Magna Powertrain

Why is This Course Important?

Achieving high product reliability has become increasingly vital for manufacturers in order to meet customer expectations amid the threat of strong global competition.  Poor reliability can doom a product and jeopardize the reputation of a brand or company.  Inadequate online reliability training courses also present financial risks from warranty, product recalls, and potential litigation.  When developing new products, it is imperative that manufacturers develop reliability specifications and utilize methods to predict and verify that those reliability specifications will be met.  This presents a difficult challenge in many industries with short product cycles and compressed product development timeframes.  This course provides an in-depth treatment of quantitative methods for predicting and demonstrating product reliability from data gathered from physical testing or from field data.

Typical Attendees

  • Product Engineers
  • Design Engineers
  • Quality Engineers
  • Reliability Engineering Training
  • Project / Program Managers
  • Manufacturing Personnel
  • Six Sigma Professionals
Enroll in the ARA Module 5 – Introduction to Reliability of Systems course

Steve is an excellent instructor who is very good on a dry topic. His application ability is great.

Bruce Schubert, BAE Systems

by Leave a Comment

ARA Module 4 – Estimation of Reliability Metrics

ARA Module 4 – Estimation of Reliability Metrics

of the Applied Reliability Analysis Course

Using Reliasoft Weibull++

This module is the core of life data analysis.  We start by providing an overview of the common methods for estimating the distribution parameters (e.g. Maximum Likelihood Estimation) and provide guidance for choosing a method.  Since quantifying uncertainty in our estimates is critical, we review the use of confidence intervals (or bounds) for this purpose.  Applying the concepts introduced previously, we learn how to utilize selected distributions to estimate reliability statistics of interest.  Treatment of censored data and multiple failure modes follow.  We also look at comparing multiple groups with respect to overall reliability performance.  Finally, we briefly look at nonparametric estimation which does not require any distribution assumption.  

A little background, motivation, full course overview, and a welcome from the instructor, Steven Wachs

The seminar was great, as usual. The books are excellent resources when I am back on the job.

— D.J. Gray Intier Automotive

Get started with the ARA Module 4 – Estimation of Reliability Metrics course today

This module-focused course includes the course information section (participants guide, textbook, and example/exercise files), plus the 11 lessons found in module 4. This module may take 5 to 6 hours to complete. Once purchased, you will have 6 months of access to the module’s content.

The full course has 11 modules, 69 lessons, and approximately 32 hours of material, examples, and exercises. Steven is available to answer your questions and discuss course topics. Once purchased, you have full access for six months. The course is on-demand, so you can engage with the course in a way that fits your schedule and interests.

The course format is voice-over slides along with a ‘live’ view of Steven showing how to use Weibull++ with examples and when reviewing exercise solutions.

The course includes the recorded presentations, a Participant Guide (copies of the slides), a Supplemental Textbook, and a Reliasoft file that includes the datasets for examples and exercises. You can download the guide, textbook, and Reliasoft files in the third lesson of the Course Introduction module. You may also view the guide and textbook within that lesson online.

The course does include some statistical background and theory, yet the emphasis is on applying reliability analysis methods using Reliasoft Weibull++. We will examine the data setup, analysis, and interpretation.

Enroll in the Full Applied Reliability Analysis course

Steve Wachs was a wonderful instructor.

Gwen Case, Schrader-Bridgeport Int’l Inc.

Enroll in the ARA Module 4 – Estimation of Reliability Metrics course

If you have already signed up for the module 1 course, login and enjoy.

Lost Password? Click here to have it emailed to you.

Training Objectives

The key training full course objectives are summarized below (highlighted objectives relate to this module)

  • Understand reliability concepts and unique aspects of reliability data
  • Understand underlying probability and statistical concepts for reliability analysis
  • Develop competency in the modeling and analysis of time-to-failure data
  • Use and interpret probability plots for distribution fitting
  • Understand reliability metrics and how to estimate and report them
  • Handle multiple failure modes in reliability estimation
  • Utilize degradation Data and models to predict failure times for life data analysis
  • Use nonparametric estimation methods when appropriate
  • Determine if reliability specifications are met (at specified confidence level) or whether design improvements are required
  • Estimate estimate uncertainty using confidence intervals and bounds
  • Estimate reliability of subsystems and systems
  • Handle basic series and parallel systems
  • Become aware of system reliability activities such as Reliability Block diagramming, Reliability importance, and Reliability allocation
  • Develop competency in the planning of reliability tests (sample sizes)
  • Use simulation to support estimation test planning
  • Develop reliability demonstration test plans (testing time vs. number of units tradeoffs)
  • Analyze existing warranty data to predict future returns
  • Analyze data from Accelerated Life Tests to estimate reliability at normal use conditions (single stress, multiple stress, time-varying stress models)
  • Plan Accelerated Life tests (sample sizes, determination of test stress combinations, allocation of units to stress levels)
  • Incorporate degradation data modeling into Accelerated Life Test analysis
  • Perform stress-strength analysis using analytical methods, software, and simulation
  • Model reliability from binary response data (i.e. pass/fail)
  • Analyze repair data from repairable systems to predict the number of failures over time, conditional reliability, and failure rates
  • Develop proficiency in the use of Reliasoft Weibull++ for Reliability analyses

Steven Wachs, Course Instructor

Steven Wachs has 25 years of wide-ranging industry experience in both technical and management positions. Steve has worked as a statistician at Ford Motor Company where he has extensive experience in the development of statistical models, reliability analysis, designed experimentation, and statistical process control.

Steve is currently a Principal Statistician at Integral Concepts, Inc. where he assists manufacturers in the application of statistical methods to reduce variation and improve quality and productivity. He also possesses expertise in the application of reliability methods to achieve robust and reliable products as well as estimate and reduce warranty. Steve regularly speaks at industry conferences and provides workshops in industrial statistical methods worldwide.

 

Thorough knowledge of subject matter and ability to communicate it – exceptional instructor.

— Steve Fleishman, Magna Powertrain

Why is This Course Important?

Achieving high product reliability has become increasingly vital for manufacturers in order to meet customer expectations amid the threat of strong global competition.  Poor reliability can doom a product and jeopardize the reputation of a brand or company.  Inadequate online reliability training courses also present financial risks from warranty, product recalls, and potential litigation.  When developing new products, it is imperative that manufacturers develop reliability specifications and utilize methods to predict and verify that those reliability specifications will be met.  This presents a difficult challenge in many industries with short product cycles and compressed product development timeframes.  This course provides an in-depth treatment of quantitative methods for predicting and demonstrating product reliability from data gathered from physical testing or from field data.

Typical Attendees

  • Product Engineers
  • Design Engineers
  • Quality Engineers
  • Reliability Engineering Training
  • Project / Program Managers
  • Manufacturing Personnel
  • Six Sigma Professionals
Enroll in the ARA Module 4 – Estimation of Reliability Metrics course

Steve is an excellent instructor who is very good on a dry topic. His application ability is great.

Bruce Schubert, BAE Systems

by Leave a Comment

ARA Module 3 – Assessing & Selecting Models

ARA Module 3 – Assessing & Selecting Models

of the Applied Reliability Analysis Course

Using Reliasoft Weibull++

Module 3 focuses on how we determine appropriate models for describing the time-to-failure data.  We introduce Probability plots and goodness-of-fit statistics that assist in determining which distributions may provide a good fit to the data.  We also learn how to handle censoring and multiple failure modes when attempting to find reasonable models for the data.

A little background, motivation, full course overview, and a welcome from the instructor, Steven Wachs

The seminar was great, as usual. The books are excellent resources when I am back on the job.

— D.J. Gray Intier Automotive

Get started with the ARA Module 3 – Assessing & Selecting Models course today

This module-focused course includes the course information section (participants guide, textbook, and example/exercise files), plus the 7 lessons found in module 3. This module may take 2 to 4 hours to complete. Once purchased, you will have 6 months of access to the module’s content.

The full course has 11 modules, 69 lessons, and approximately 32 hours of material, examples, and exercises. Steven is available to answer your questions and discuss course topics. Once purchased, you have full access for six months. The course is on-demand, so you can engage with the course in a way that fits your schedule and interests.

The course format is voice-over slides along with a ‘live’ view of Steven showing how to use Weibull++ with examples and when reviewing exercise solutions.

The course includes the recorded presentations, a Participant Guide (copies of the slides), a Supplemental Textbook, and a Reliasoft file that includes the datasets for examples and exercises. You can download the guide, textbook, and Reliasoft files in the third lesson of the Course Introduction module. You may also view the guide and textbook within that lesson online.

The course does include some statistical background and theory, yet the emphasis is on applying reliability analysis methods using Reliasoft Weibull++. We will examine the data setup, analysis, and interpretation.

Enroll in the Full Applied Reliability Analysis course

Steve Wachs was a wonderful instructor.

Gwen Case, Schrader-Bridgeport Int’l Inc.

Enroll in the ARA Module 3 – Assessing and Selecting Models course

If you have already signed up for the module 1 course, login and enjoy.

Lost Password? Click here to have it emailed to you.

Training Objectives

The key training full course objectives are summarized below (highlighted objectives relate to this module)

  • Understand reliability concepts and unique aspects of reliability data
  • Understand underlying probability and statistical concepts for reliability analysis
  • Develop competency in the modeling and analysis of time-to-failure data
  • Use and interpret probability plots for distribution fitting
  • Understand reliability metrics and how to estimate and report them
  • Handle multiple failure modes in reliability estimation
  • Utilize degradation Data and models to predict failure times for life data analysis
  • Use nonparametric estimation methods when appropriate
  • Determine if reliability specifications are met (at specified confidence level) or whether design improvements are required
  • Estimate estimate uncertainty using confidence intervals and bounds
  • Estimate reliability of subsystems and systems
  • Handle basic series and parallel systems
  • Become aware of system reliability activities such as Reliability Block diagramming, Reliability importance, and Reliability allocation
  • Develop competency in the planning of reliability tests (sample sizes)
  • Use simulation to support estimation test planning
  • Develop reliability demonstration test plans (testing time vs. number of units tradeoffs)
  • Analyze existing warranty data to predict future returns
  • Analyze data from Accelerated Life Tests to estimate reliability at normal use conditions (single stress, multiple stress, time-varying stress models)
  • Plan Accelerated Life tests (sample sizes, determination of test stress combinations, allocation of units to stress levels)
  • Incorporate degradation data modeling into Accelerated Life Test analysis
  • Perform stress-strength analysis using analytical methods, software, and simulation
  • Model reliability from binary response data (i.e. pass/fail)
  • Analyze repair data from repairable systems to predict the number of failures over time, conditional reliability, and failure rates
  • Develop proficiency in the use of Reliasoft Weibull++ for Reliability analyses

Steven Wachs, Course Instructor

Steven Wachs has 25 years of wide-ranging industry experience in both technical and management positions. Steve has worked as a statistician at Ford Motor Company where he has extensive experience in the development of statistical models, reliability analysis, designed experimentation, and statistical process control.

Steve is currently a Principal Statistician at Integral Concepts, Inc. where he assists manufacturers in the application of statistical methods to reduce variation and improve quality and productivity. He also possesses expertise in the application of reliability methods to achieve robust and reliable products as well as estimate and reduce warranty. Steve regularly speaks at industry conferences and provides workshops in industrial statistical methods worldwide.

 

Thorough knowledge of subject matter and ability to communicate it – exceptional instructor.

— Steve Fleishman, Magna Powertrain

Why is This Course Important?

Achieving high product reliability has become increasingly vital for manufacturers in order to meet customer expectations amid the threat of strong global competition.  Poor reliability can doom a product and jeopardize the reputation of a brand or company.  Inadequate online reliability training courses also present financial risks from warranty, product recalls, and potential litigation.  When developing new products, it is imperative that manufacturers develop reliability specifications and utilize methods to predict and verify that those reliability specifications will be met.  This presents a difficult challenge in many industries with short product cycles and compressed product development timeframes.  This course provides an in-depth treatment of quantitative methods for predicting and demonstrating product reliability from data gathered from physical testing or from field data.

Typical Attendees

  • Product Engineers
  • Design Engineers
  • Quality Engineers
  • Reliability Engineering Training
  • Project / Program Managers
  • Manufacturing Personnel
  • Six Sigma Professionals
Enroll in the ARA Module 3 – Assessing and Selecting Models course

Steve is an excellent instructor who is very good on a dry topic. His application ability is great.

Bruce Schubert, BAE Systems

by Leave a Comment

ARA Module 2 – Probability & Reliability Statistics

ARA Module 2 – Probability & Reliability Statistics

of the Applied Reliability Analysis Course

Using Reliasoft Weibull++

In preparation for the reliability methods and tools to follow, this module covers many of the fundamental building blocks.  Since Reliability is a probability, we review some essential probability ideas and rules.  We introduce the concept of conditional probability since it plays a  role in various methods such as warranty forecasting and burn-in.  We discuss probability models that may be considered in describing time-to-failure data with some emphasis on the Weibull distribution.  The Weibull distribution is very popular due to its flexibility and meaningful parameters although we should not limit ourselves solely to this model.  Finally, we discuss some useful discrete distribution models and their applications to reliability.  

A little background, motivation, full course overview, and a welcome from the instructor, Steven Wachs

Use the course menu to navigate to the first lesson

The seminar was great, as usual. The books are excellent resources when I am back on the job.

— D.J. Gray Intier Automotive

Get started with the ARA Module 2 – Probability & Reliability Statistics course today

This module-focused course includes the course information section (participants guide, textbook, and example/exercise files), plus the 7 lessons found in module 2. This module may take 3 to 4 hours to complete. Once purchased, you will have 6 months of access to the module’s content.

The full course has 11 modules, 69 lessons, and approximately 32 hours of material, examples, and exercises. Steven is available to answer your questions and discuss course topics. Once purchased, you have full access for six months. The course is on-demand, so you can engage with the course in a way that fits your schedule and interests.

The course format is voice-over slides along with a ‘live’ view of Steven showing how to use Weibull++ with examples and when reviewing exercise solutions.

The course includes the recorded presentations, a Participant Guide (copies of the slides), a Supplemental Textbook, and a Reliasoft file that includes the datasets for examples and exercises. You can download the guide, textbook, and Reliasoft files in the third lesson of the Course Introduction module. You may also view the guide and textbook within that lesson online.

The course does include some statistical background and theory, yet the emphasis is on applying reliability analysis methods using Reliasoft Weibull++. We will examine the data setup, analysis, and interpretation.

Enroll in the Full Applied Reliability Analysis course

Steve Wachs was a wonderful instructor.

Gwen Case, Schrader-Bridgeport Int’l Inc.

Enroll in the ARA Module 2 – Probability and Reliability Statistics course

If you have already signed up for the module 1 course, login and enjoy.

Lost Password? Click here to have it emailed to you.

Training Objectives

The key training full course objectives are summarized below (highlighted objectives relate to this module)

  • Understand reliability concepts and unique aspects of reliability data
  • Understand underlying probability and statistical concepts for reliability analysis
  • Develop competency in the modeling and analysis of time-to-failure data
  • Use and interpret probability plots for distribution fitting
  • Understand reliability metrics and how to estimate and report them
  • Handle multiple failure modes in reliability estimation
  • Utilize degradation Data and models to predict failure times for life data analysis
  • Use nonparametric estimation methods when appropriate
  • Determine if reliability specifications are met (at specified confidence level) or whether design improvements are required
  • Estimate estimate uncertainty using confidence intervals and bounds
  • Estimate reliability of subsystems and systems
  • Handle basic series and parallel systems
  • Become aware of system reliability activities such as Reliability Block diagramming, Reliability importance, and Reliability allocation
  • Develop competency in the planning of reliability tests (sample sizes)
  • Use simulation to support estimation test planning
  • Develop reliability demonstration test plans (testing time vs. number of units tradeoffs)
  • Analyze existing warranty data to predict future returns
  • Analyze data from Accelerated Life Tests to estimate reliability at normal use conditions (single stress, multiple stress, time-varying stress models)
  • Plan Accelerated Life tests (sample sizes, determination of test stress combinations, allocation of units to stress levels)
  • Incorporate degradation data modeling into Accelerated Life Test analysis
  • Perform stress-strength analysis using analytical methods, software, and simulation
  • Model reliability from binary response data (i.e. pass/fail)
  • Analyze repair data from repairable systems to predict the number of failures over time, conditional reliability, and failure rates
  • Develop proficiency in the use of Reliasoft Weibull++ for Reliability analyses

Steven Wachs, Course Instructor

Steven Wachs has 25 years of wide-ranging industry experience in both technical and management positions. Steve has worked as a statistician at Ford Motor Company where he has extensive experience in the development of statistical models, reliability analysis, designed experimentation, and statistical process control.

Steve is currently a Principal Statistician at Integral Concepts, Inc. where he assists manufacturers in the application of statistical methods to reduce variation and improve quality and productivity. He also possesses expertise in the application of reliability methods to achieve robust and reliable products as well as estimate and reduce warranty. Steve regularly speaks at industry conferences and provides workshops in industrial statistical methods worldwide.

 

Thorough knowledge of subject matter and ability to communicate it – exceptional instructor.

— Steve Fleishman, Magna Powertrain

Why is This Course Important?

Achieving high product reliability has become increasingly vital for manufacturers in order to meet customer expectations amid the threat of strong global competition.  Poor reliability can doom a product and jeopardize the reputation of a brand or company.  Inadequate online reliability training courses also present financial risks from warranty, product recalls, and potential litigation.  When developing new products, it is imperative that manufacturers develop reliability specifications and utilize methods to predict and verify that those reliability specifications will be met.  This presents a difficult challenge in many industries with short product cycles and compressed product development timeframes.  This course provides an in-depth treatment of quantitative methods for predicting and demonstrating product reliability from data gathered from physical testing or from field data.

Typical Attendees

  • Product Engineers
  • Design Engineers
  • Quality Engineers
  • Reliability Engineering Training
  • Project / Program Managers
  • Manufacturing Personnel
  • Six Sigma Professionals
Enroll in the ARA Module 2 – Probability and Reliability Statistics course

Steve is an excellent instructor who is very good on a dry topic. His application ability is great.

Bruce Schubert, BAE Systems

by Leave a Comment

ARA Module 1 – Reliability Concepts and Data

ARA Module 1 – Reliability Concepts and Data

of the Applied Reliability Analysis Course

Using Reliasoft Weibull++

In this introductory module, we define Reliability and cover many important reliability concepts.  We discuss why reliability performance is so important and the types of questions that may be answered by analyzing failure data.  Different types of reliability data are reviewed.  We introduce the concept of censored data which allows us to correctly utilize partial or incomplete data in the analysis of test or field data.  We cover the Bathtub Curve which illustrates the types of failures that may occur over a product’s lifetime.  Finally, we introduce the reliability function and discuss product reliability goals.

A little background, motivation, full course overview, and a welcome from the instructor, Steven Wachs

The seminar was great, as usual. The books are excellent resources when I am back on the job.

— D.J. Gray Intier Automotive

Get started with the ARA Module 1 – Reliability Concepts and Data course today

This module-focused course includes the course information section (participants guide, textbook, and example/exercise files), plus the 6 lessons found in module 1. This module may take 2 to 3 hours to complete. Once purchased, you will have 6 months of access to the module’s content.

The full course has 11 modules, 69 lessons, and approximately 32 hours of material, examples, and exercises. Steven is available to answer your questions and discuss course topics. Once purchased, you have full access for six months. The course is on-demand, so you can engage with the course in a way that fits your schedule and interests.

The course format is voice-over slides along with a ‘live’ view of Steven showing how to use Weibull++ with examples and when reviewing exercise solutions.

The course includes the recorded presentations, a Participant Guide (copies of the slides), a Supplemental Textbook, and a Reliasoft file that includes the datasets for examples and exercises. You can download the guide, textbook, and Reliasoft files in the third lesson of the Course Introduction module. You may also view the guide and textbook within that lesson online.

The course does include some statistical background and theory, yet the emphasis is on applying reliability analysis methods using Reliasoft Weibull++. We will examine the data setup, analysis, and interpretation.

Enroll in the Full Applied Reliability Analysis course

Steve Wachs was a wonderful instructor.

Gwen Case, Schrader-Bridgeport Int’l Inc.

Enroll in the ARA Module 1 – Reliability Concepts and Data course

If you have already signed up for the module 1 course, login and enjoy.

Lost Password? Click here to have it emailed to you.

Training Objectives

The key training full course objectives are summarized below (highlighted objectives relate to this module)

  • Understand reliability concepts and unique aspects of reliability data
  • Understand underlying probability and statistical concepts for reliability analysis
  • Develop competency in the modeling and analysis of time-to-failure data
  • Use and interpret probability plots for distribution fitting
  • Understand reliability metrics and how to estimate and report them
  • Handle multiple failure modes in reliability estimation
  • Utilize degradation Data and models to predict failure times for life data analysis
  • Use nonparametric estimation methods when appropriate
  • Determine if reliability specifications are met (at specified confidence level) or whether design improvements are required
  • Estimate estimate uncertainty using confidence intervals and bounds
  • Estimate reliability of subsystems and systems
  • Handle basic series and parallel systems
  • Become aware of system reliability activities such as Reliability Block diagramming, Reliability importance, and Reliability allocation
  • Develop competency in the planning of reliability tests (sample sizes)
  • Use simulation to support estimation test planning
  • Develop reliability demonstration test plans (testing time vs. number of units tradeoffs)
  • Analyze existing warranty data to predict future returns
  • Analyze data from Accelerated Life Tests to estimate reliability at normal use conditions (single stress, multiple stress, time-varying stress models)
  • Plan Accelerated Life tests (sample sizes, determination of test stress combinations, allocation of units to stress levels)
  • Incorporate degradation data modeling into Accelerated Life Test analysis
  • Perform stress-strength analysis using analytical methods, software, and simulation
  • Model reliability from binary response data (i.e. pass/fail)
  • Analyze repair data from repairable systems to predict the number of failures over time, conditional reliability, and failure rates
  • Develop proficiency in the use of Reliasoft Weibull++ for Reliability analyses

Steven Wachs, Course Instructor

Steven Wachs has 25 years of wide-ranging industry experience in both technical and management positions. Steve has worked as a statistician at Ford Motor Company where he has extensive experience in the development of statistical models, reliability analysis, designed experimentation, and statistical process control.

Steve is currently a Principal Statistician at Integral Concepts, Inc. where he assists manufacturers in the application of statistical methods to reduce variation and improve quality and productivity. He also possesses expertise in the application of reliability methods to achieve robust and reliable products as well as estimate and reduce warranty. Steve regularly speaks at industry conferences and provides workshops in industrial statistical methods worldwide.

 

Thorough knowledge of subject matter and ability to communicate it – exceptional instructor.

— Steve Fleishman, Magna Powertrain

Why is This Course Important?

Achieving high product reliability has become increasingly vital for manufacturers in order to meet customer expectations amid the threat of strong global competition.  Poor reliability can doom a product and jeopardize the reputation of a brand or company.  Inadequate online reliability training courses also present financial risks from warranty, product recalls, and potential litigation.  When developing new products, it is imperative that manufacturers develop reliability specifications and utilize methods to predict and verify that those reliability specifications will be met.  This presents a difficult challenge in many industries with short product cycles and compressed product development timeframes.  This course provides an in-depth treatment of quantitative methods for predicting and demonstrating product reliability from data gathered from physical testing or from field data.

Typical Attendees

  • Product Engineers
  • Design Engineers
  • Quality Engineers
  • Reliability Engineering Training
  • Project / Program Managers
  • Manufacturing Personnel
  • Six Sigma Professionals
Enroll in the ARA Module 1 – Reliability Concepts and Data course

Steve is an excellent instructor who is very good on a dry topic. His application ability is great.

Bruce Schubert, BAE Systems

by 4 Comments

Applied Reliability Analysis

Applied Reliability Analysis Course

Using Reliasoft Weibull++

A little background, motivation, course overview, and a welcome from the instructor, Steven Wachs

The seminar was great, as usual. The books are excellent resources when I am back on the job.

— D.J. Gray Intier Automotive

Get started with the Applied Reliability Analysis course today

This course has 11 modules, 69 lessons, and approximately 32 hours of material, examples, and exercises. Steven is available to answer your questions and discuss course topics. Once purchased, you have full access for six months. The course is on-demand, so you can engage with the course in a way that fits your schedule and interests.

The course format is voice-over slides along with a ‘live’ view of Steven showing how to use Weibull++ with examples and when reviewing exercise solutions.

The course includes the recorded presentations, a Participant Guide (copies of the slides), a Supplemental Textbook, and a Reliasoft file that includes the datasets for examples and exercises. You can download the guide, textbook, and Reliasoft files in the third lesson of the Course Introduction module. You may also view the guide and textbook within that lesson online.

The course does include some statistical background and theory, yet the emphasis is on applying reliability analysis methods using Reliasoft Weibull++. We will examine the data setup, analysis, and interpretation.

Steve Wachs was a wonderful instructor.

Gwen Case, Schrader-Bridgeport Int’l Inc.

Enroll in the Applied Reliability Analysis course

If you would like to enroll in just one or a few modules, or you have a team or group all ready to enroll in the course, please visit the course purchase options page for details.

If you have already signed up for the course, login and enjoy.

Lost Password? Click here to have it emailed to you.

Training Objectives

The key training objectives are summarized below:

  • Understand reliability concepts and unique aspects of reliability data
  • Understand underlying probability and statistical concepts for reliability analysis
  • Develop competency in the modeling and analysis of time-to-failure data
  • Use and interpret probability plots for distribution fitting
  • Understand reliability metrics and how to estimate and report them
  • Handle multiple failure modes in reliability estimation
  • Utilize degradation Data and models to predict failure times for life data analysis
  • Use nonparametric estimation methods when appropriate
  • Determine if reliability specifications are met (at specified confidence level) or whether design improvements are required
  • Estimate estimate uncertainty using confidence intervals and bounds
  • Estimate reliability of subsystems and systems
  • Handle basic series and parallel systems
  • Become aware of system reliability activities such as Reliability Block diagramming, Reliability importance, and Reliability allocation
  • Develop competency in the planning of reliability tests (sample sizes)
  • Use simulation to support estimation test planning
  • Develop reliability demonstration test plans (testing time vs. number of units tradeoffs)
  • Analyze existing warranty data to predict future returns
  • Analyze data from Accelerated Life Tests to estimate reliability at normal use conditions (single stress, multiple stress, time-varying stress models)
  • Plan Accelerated Life tests (sample sizes, determination of test stress combinations, allocation of units to stress levels)
  • Incorporate degradation data modeling into Accelerated Life Test analysis
  • Perform stress-strength analysis using analytical methods, software, and simulation
  • Model reliability from binary response data (i.e. pass/fail)
  • Analyze repair data from repairable systems to predict the number of failures over time, conditional reliability, and failure rates
  • Develop proficiency in the use of Reliasoft Weibull++ for Reliability analyses

Steven Wachs, Course Instructor

Steven Wachs has 25 years of wide-ranging industry experience in both technical and management positions. Steve has worked as a statistician at Ford Motor Company where he has extensive experience in the development of statistical models, reliability analysis, designed experimentation, and statistical process control.

Steve is currently a Principal Statistician at Integral Concepts, Inc. where he assists manufacturers in the application of statistical methods to reduce variation and improve quality and productivity. He also possesses expertise in the application of reliability methods to achieve robust and reliable products as well as estimate and reduce warranty. Steve regularly speaks at industry conferences and provides workshops in industrial statistical methods worldwide.

 

Thorough knowledge of subject matter and ability to communicate it – exceptional instructor.

— Steve Fleishman, Magna Powertrain

Why is This Course Important?

Achieving high product reliability has become increasingly vital for manufacturers in order to meet customer expectations amid the threat of strong global competition.  Poor reliability can doom a product and jeopardize the reputation of a brand or company.  Inadequate online reliability training courses also present financial risks from warranty, product recalls, and potential litigation.  When developing new products, it is imperative that manufacturers develop reliability specifications and utilize methods to predict and verify that those reliability specifications will be met.  This presents a difficult challenge in many industries with short product cycles and compressed product development timeframes.  This course provides an in-depth treatment of quantitative methods for predicting and demonstrating product reliability from data gathered from physical testing or from field data.

Typical Attendees

  • Product Engineers
  • Design Engineers
  • Quality Engineers
  • Reliability Engineering Training
  • Project / Program Managers
  • Manufacturing Personnel
  • Six Sigma Professionals
Enroll in the Applied Reliability Analysis course

If you would like to enroll in just one or few modules, or you have a team or group all ready to enroll in the course, please visit the course purchase options page for details.

Steve is an excellent instructor who is very good on a dry topic. His application ability is great.

Bruce Schubert, BAE Systems

by Leave a Comment

FMEA Introduction

FMEA Introduction

The FMEA Introduction course

Offered by The Luminous Group. Principle instructor Rich Nave.

Course Description

This short introductory course provides an online learning opportunity to grasp the fundamentals of Failure Mode and Effects Analysis (FMEA)

Risk Assessment and Risk Mitigation are essential parts of product and process development.  Proactively identifying risk and taking action to reduce or eliminate the impact these risks pose to a project are critical to being competitive in a fast-paced environment. Failure Mode and Effects Analysis (FMEA) is a globally recognized best practice for risk assessments. 

This course will introduce you to the key concepts of Failure Mode and Effect Analysis including why it adds value. This methodology supports robust practice for teams to investigate and document risks and actions by the team to reduce those risks.

Get Started with FMEA Introduction Today

$9.99 for 90 day access

Enroll in the FMEA Introduction course

Content Summary

The following content will be highlighted in a go at your own pace on-line learning space.

  • Explanation of FMEA basics, including the three main types of FMEAs
  • Understanding FMEA as a dynamic document.
  • Content is presented in easy-to-understand, bite-sized portions through reading materials and videos.
  • Participants have the chance to revisit content for better understanding.
  • Includes process self-assessment and opportunities for self-reflection.
  • Concludes with a learning assessment to gauge understanding.
  • Key topics covered include:
    • What is FMEA?
    • Why Use FMEA?
    • Types of FMEAs
    • Linkages Between Types of FMEAs
    • Prevention and Detection Controls
    • Risk Ranking
    • FMEA as a Living Document

Training Objectives

Upon completion of this course, you will be able to:

  • Recognize the value of FMEA 
  • Distinguish the relationship and linkages between different types of FMEA
  • Recognize how FMEAs link to other documents
  • Identify how the FMEA is used as a living document

Course Details

Duration: Self-paced, typically 20 to 30 minutes.

Prerequisites: Basic knowledge of product design processes or manufacturing workflow.

Pricing: $9.99 (Contact us for discounts available for corporate groups.)

Get Started with FMEA Introduction Today

Enroll in the FMEA Introduction course

If you have already signed up for the course, login and enjoy.

Lost Password? Click here to have it emailed to you.

About The Luminous Group

The Luminous Group works with Engineering, Manufacturing, and Quality leaders who struggle with:

  • Unexpected or repeat quality issues
  • Reducing costs associated with poor quality
  • Ineffective or inconsistent internal quality audits
  • A lack of leadership, structure, or skills for problem-solving and continuous improvement

Since 1999, we’ve helped hundreds of companies—and thousands of team members—become more empowered, effective, and efficient with enlightening audits, training, and process improvement consulting.

www.LuminousGroup.com

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Fault Tree Analysis (FTA)

Fault Tree Analysis (FTA)

Reliability happens at the point of DECISION

Reliability doesn’t just happen. Following standards, doing what worked 10 years ago or any other approach to reliability engineering that doesn’t focus on what your system is today won’t make reliability happen.

Fault trees are great at modeling system reliability. They are one of several tools that can help you turn what you know about component or subsystem failure characteristics into an understanding of system reliability characteristics. Which lets you measure reliability.

But measuring reliability is one thing. Improving reliability is a much bigger thing.

Good reliability decisions are based on 
knowing HOW your system will fail

Fault trees are a great Root Cause Analysis (RCA) tool. They can really help you and your team identify the potential causes of failure, which then focuses your investigation on what really happened.

But it is much better to prevent failures from occurring. Making your first design a reliable design means you need to know how your system will fail … from the first day of design.

Fault Tree Analysis (FTA) is a great 
tool for working this out

This course is one of the few courses I have ever done that has actually made me want to come back and do more reliability engineering courses. The animations are fantastic, there are not thousands of equations, and I felt like I understood why I needed to learn each topic before I started. I cannot recommend this course enough!

— David (rail industry)

Get started with Fault Tree Analysis today

Enroll in the Fault Tree Analysis course.

If you have already signed up for the course, log in and enjoy.

Lost Password? Click here to have it emailed to you.

Course Description and Overview

The 4-hour, 11-module Fault Tree Analysis (FTA) Course teaches you how to use fault trees to achieve important outcomes supporting reliability performance.

Fault trees are visual representation methodologies that represent our understanding of how faults progress to a state of failure. 

Fault trees can be used to model system reliability where the reliability performance characteristics of components are used to determine system reliability performance characteristics. This allows us to model Time to Failure (TTF) at a system level if we have a good understanding of component TTF. This can then be used to inform things like warranty period determination or reliability at any point in usage.

Fault trees can also be used from the perspective of Root Cause Analysis (RCA). This usually occurs when we have observed a failure (or undesirable event) and want to ‘collectively brainstorm’ a series of explanations as to why it occurred. Fault trees used in this way can be used to identify likely ‘root causes’ that can either be the subject of further investigation or be designed out of the system. Fault trees used in this context support ‘reliability improvement’ more than ‘reliability measurement.’ 

Fault trees in this way can be used in a fundamentally more valuable context where we focus on preventing problems like failure before they occur. Fault trees used in this way are often parts of larger proactive reliability engineering activities like Failure Mode and Effects Analyses (FMEAs). If failure is defined as any event where we fail to meet our customer or user expectations, fault trees can help us do robust, customer-centric design. This is where we prioritize what features matter the most to our customers, and we incorporate really simple design changes very early in the production lifecycle to become or remain an industry leader.

Students who design, manufacture, or need to otherwise manage any sort of product or equipment will benefit from this course. FTA can be used for modeling TTF and informing key business plan decisions. FTA can be used to identify root causes of failure – both in the past and in the future. This means that FTA can be used to prevent problems, including issues that may introduce production costs and delays. FTA can be used to identify the VITAL FEW problems and issues our product, systems or services need to focus on.

Medium or Delivery Mode

This FTA Course is made up of 

11 lessons

that take you through the fundamentals of FTA, broken down into ‘three’ perspectives: system reliability modeling; RCA; and robust customer-centric design. These modules are based on an example that is iteratively developed throughout the course, with students completing exercises and questions in the workbook.

There is a total of 

4 hours of lessons.

This course will be delivered through

Self-paced video lessons.

So, regardless of where you find yourself in life, you 
will be able to do this course when it suits you.

Here is what you get. You get

1-year access

There will always be new developments in reliability engineering, and we will keep finding better ways to tell the story. 
So, as we make module updates, you will continue to get access to the course for one year from the date of purchase.

Then there is

 Ongoing expert Q&A.

I will be available to answer your questions for 12 months after completion of the course. See the course Materials tab to find contact options.

Who is your teacher? Dr. Chris Jackson

Dr Jackson holds a Ph.D. and MSc in Reliability Engineering from the University of Maryland’s Center of Risk and Reliability. He also holds a BE in Mechanical Engineering, a Masters of Military Science from the Australian National University (ANU) and has substantial experience in the field of leadership, management, risk, reliability and maintainability. He is a Certified Reliability Engineer (CRE) through the American Society of Quality (ASQ) and a Chartered Professional Engineer (CPEng) through Engineers Australia.

Dr Jackson is an Accendo Reliability Thought Leader. Was the inaugural director of the University of California, Los Angeles (UCLA’s) Center of Reliability and Resilience Engineering and the founder of its Center for the Safety and Reliability of Autonomous Systems (SARAS). He has had an extensive career as a Senior Reliability Engineer in the Australian Defence Force and is the Director of Acuitas Reliability Pty Ltd.

He has supported many complex and material systems to develop their reliability performance and assisted in providing reliability management frameworks that support business outcomes (that is, making more money). He has been a reliability management consultant to many companies across industries ranging from medical devices to small satellites. He has also led initiatives in complementary fields such as systems engineering and performance-based management frameworks (PBMFs). He is the author of two reliability engineering books, a co-author of another, and several journal articles and conference papers.

What you will receive

Access to all 4 hours of lesson videos

The comprehensive electronic course notes are an interactive PDF document that allows you to take notes using your computer or tablet.

Direct access to Chris for questions about the course content or its application.

Technical support for any issue accessing or viewing the course content from Accendo Reliability.

Student Learning Objectives

Students who complete this course will be able to do the following:

  • Describe fault trees and how they are constructed
  • Understand the different perspectives from which fault trees are used and how this affects their employment
  • Identify which decisions may benefit from FTA, and which perspective is relevant
  • Construct fault trees that model system reliability
  • Understand ‘logic gates’ and how they are included in a fault tree
  • Understand basic system reliability configurations that include parallel, series, ‘k out of n’ configurations
  • Integrate fault trees with other modeling methodologies including Reliability Block Diagrams (RBDs), success trees, Event Trees (ETs) and other fault trees
  • Analyze system reliability using a fault tree system reliability model and component reliability performance characteristics
  • Model basic dependent failure scenarios including Common Cause Failure
  • Understand the different redundancy configurations represented by fault tree ‘AND’ gates that include load sharing and switching systems
  • List key limitations of FTA software
  • Construct a fault tree that models ‘causality’ to help identify potential root causes of failure (both past and future)
  • Identify potential root causes of observed failure using FTA (as part of RCA)
  • Identify potential root causes of potential failure using FTA (as part of FMEA)
  • Design robust, customer-centric products, systems and services using FTA based on customer expectation
  • Understand system ‘cut sets’ and how they relate to reliability performance characteristics
  • Identify ‘cut sets’ from a fault tree that models system reliability
  • Create FTA strategies that efficiently and effectively using teams (as part of a group activity)
  • List the pros of FTA to help identify when fault trees can support a specific decision
  • List the cons of FTA to help identify when fault trees can NOT support a specific decision

Learning Resouces

All students will need to have a computer or laptop with speakers, a microphone and the capability of hosting Zoom TM video conferencing software. You will also need to prepare yourself to be an ‘online student’ and make sure that wherever you are, you have set yourself up for learning. More help can be found at the How to be a Successful Online Student page.

You should have a pen and note-taking paper. You do not need any textbooks to undertake this course, but if you are interested in learning more about reliability engineering, then we recommend Reliability Engineering and Management.  

You will also need access to Microsoft PowerPoint for a class exercise. You will be required to overlay certain statistical plots as part of a class exercise.

We also highly recommend becoming a member at www.accendoreliability.com. This is a free resource with podcasts, webinars, articles and books that can help you remain up to date with reliability engineering developments. 

There is no assessment or exam you have to pass in order to complete this course.

by 4 Comments

Accendo Reliability Webinar Series

Accendo Reliability Webinar Series

Recordings of live webinar events providing practical and informative educational material for your professional development.

A mix of topics ranging across the field of reliability engineering and related fields. Formats range from how-to tutorials to thought-provoking essays. Topics include fundamental statistical concepts to overarching program management.

If you have already enrolled to view the recordings, login to view all the recorded webinars. If not, then Enroll above.

Lost Password? Click here to have it emailed to you.

Join us for these upcoming live events. Catch up with past events via the podcast series or the recorded videos of the events found here. If you have questions before, during, or after an event – just let us know. We do enjoy hearing from you and assisting you to improve your abilities.

I want to tell you that I have gone through many webinars on Accendo Reliability and found them very useful. I am new to Reliability Engineering and very keen to learn it and apply it in my organization.

– Ankur Sharmapu