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Key Teaching Principle #5 Convey Interest and Passion

As covered in the first article in this series, Principles of Effective Teaching, reliability engineers, FMEA team leaders, and other quality and reliability professionals are often called upon to teach the principles of reliability or FMEA. Whether you are a student who wants to enhance your learning experience, an instructor who wants to improve teaching results, or an engineer who wishes to convey knowledge to another person, this series will offer practical knowledge and advice.

Conveying Interest and Passion When Teaching

“A teacher who is attempting to teach without inspiring the pupil with a desire to learn is hammering on cold iron.” Horace Mann

What is Interest and how does it enhance learning?

The definition of interest is “a feeling that accompanies or causes special attention to something or someone.” [Read more…]

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Project Recovery: A Blame Game?

Project Recovery: A Blame Game?

Guest Post by Malcolm Peart (first posted on CERM ® RISK INSIGHTS – reposted here with permission)

Projects go wrong.  Despite some people’s best efforts, hopes to the contrary, or helpless denials, that’s a fact.  ‘Best effort’ is sometimes not good enough to help a failing project recover, ‘hope’ can merely be unfounded optimism and denial in the light of facts is just part of the grief cycle.

Nobody really wants to fail, very few like it, and even fewer will enjoy it.  Those that planned a project did not purposely plan to fail.  Perhaps there may have been a bit of a gamble with a tendency towards optimism rather than applying the caution of pessimism.  Projects are about risk as well as opportunity and as the idiom goes, “Nothing ventured…nothing gained” but not every cloud has a silver lining.

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DOE-4: Case Study in Design of Experiments to Maximize Fatigue Strength of Crankshaft

DOE-4: Case Study in Design of Experiments to Maximize Fatigue Strength of Crankshaft

Hemant Urdhwareshe, Director of Institute of Quality and Reliability presents case study to maximize fatigue strength of crankshaft using design of experiments using SigmaXL Template of Full Factorial Design with three factors each at two levels.

Hemant is Fellow of ASQ and possesses five certifications from ASQ including Six Sigma Master Black Belt and Reliability Engineer. It is recommended that viewers first watch the previous videos DOE-1, DOE-2 and DOE-3 before watching this video. SigmaXL trial version can be downloaded from www.sigmaxl.com.

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Communicating Reliability Starts with Being Able to Quickly Define It

Communicating Reliability Starts with Being Able to Quickly Define It

Reliability is one of the most overworked and misunderstood words in the world of facilities and infrastructure. Reliability is also one of the most powerful and important words. Properly evaluating and communicating reliability resolves risk, safety, quality, compliance, and human performance. Reliability also frames a powerful and effective systems approach instead of leaving gaps by cobbling together individual assets and components. Effectively communicating reliability starts with being able to quickly define it, [Read more…]

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Do You Contract Your Maintenance – Yes or No?

Do You Contract Your Maintenance – Yes or No?

Guest post By Arnold (Arnie) F. Newland, CMRP

I have led internal maintenance teams towards world class reliability, I have outsourced specialized maintenance functions (predictive technologies) and I have worked with companies outsourcing all maintenance. 

Maintenance outsourcing continues to grow with 65% of large companies outsourcing some maintenance..but perhaps for the wrong reasons.

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Risk Inherent in Modern Society

Risk Inherent in Modern Society

Guest Post by Bill Pomfret (first posted on CERM ® RISK INSIGHTS – reposted here with permission)

Just how safe is “safe”? Should working in a chemical plant have the same level of risk as skydiving (which kills about 40 people per year in the U.S.A Should working in a plant be as safe as driving your car? Or should it be as safe as flying in a plane, which is safer than driving a car by two orders of magnitude?

While the term FAR may be simple to understand and may represent a useful yardstick, many companies, especially in the U.S., are unwilling to put such targets in writing. Imagine walking into company XYZ’s plush world headquarters office and on the wall in the reception area is a sign that reads, “We at XYZ consider it tolerable to kill 4 people per 100-million-man hours.” The lawyers would have a field day! However, as we shall see, some organizations have established such quantified risk targets.

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DOE-3: Coded and Uncoded Values & Establishing Regression Equation

DOE-3: Coded and Uncoded Values & Establishing Regression Equation

I am happy to share my third video on Design of Experiments (DOE-3). This is the third video in our series on Design of Experiments. It is recommended that viewers should watch the first two videos (doe-1-introduction-to-design-of-experiments and DOE-2: DOE Case Study of Spot Welding) before watching this video for better learning and understanding.

In this video, we have explained how to convert uncoded values of factor-levels to coded values and vice versa. We have also explained how to create a linear regression equation from the results of a full factorial two-level experiment.

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Student Questions from My Root Cause Analysis Class, Part 1

Student Questions from My Root Cause Analysis Class, Part 1

Since launching my Root Cause Analysis class just over 5 years ago, I count myself remarkably fortunate to have been a part of the learning journeys of the 14,000+ students who have taken it. And a welcomed part of teaching courses online is fielding questions that come from students. In addition to clarifying for them various technical points of the course, I also get a “behind the curtains” look at the general training gaps in the quality profession. Afterall, that one student’s question may be in lingering in the minds of countless other quality professionals as well.

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Parametric versus Non-Parametric Life Estimations – Sacrificing Reality for Elegance

Parametric versus Non-Parametric Life Estimations – Sacrificing Reality for Elegance

A parametric Life Analysis involves “forcing” or “imposing” a distribution’s parameters on a data set in order to obtain the “best fit”. However, it can lead to errors in results. The non-parametric estimation suggests that there are other approaches though not necessarily the easiest or “most elegant” ones. In the field of reliability engineering, we tend to like something so much that we use them in every “sauce”. A classic example is the Weibull Distribution. It has become so popular that Life Analysis is also known as a “Weibull Analysis”. As a reminder, the Weibull distribution is only one parametric distribution amongst a myriad of others, invented by Walodi Weibull in 1937. Dr Bob Abernathy’s New Weibull Handbook1 quotes: “the Weibull distribution provides reasonably accurate failure and failure forecasts……”. Thus, parametric distributions are good enough but not perfect to make a decision.

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No Evidence of Correlation: Field failures and Traditional Reliability Engineering

No Evidence of Correlation: Field failures and Traditional Reliability Engineering

Historically, Reliability Engineering of Electronics has been dominated by the belief that 1) The life or percentage of complex hardware failures that occur over time can be estimated, predicted, or modeled, and 2) the Reliability of electronic systems can be calculated or estimated through statistical and probabilistic methods to improve hardware reliability.  The amazing thing about this is that during the many decades that reliability

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