Accendo Reliability

Your Reliability Engineering Professional Development Site

All articles listed in reverse chronological order.

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Top 10 Reasons Maintenance and Reliability Initiatives Fail

Top 10 Reasons Maintenance and Reliability Initiatives Fail

Guest post by Kenneth Latino.

I have been in the business of maintenance and reliability for nearly 35 years. I have had the luxury of working with many industries during my career both as a practitioner in a large paper mill and as a maintenance/reliability consultant. I have been able to see what works and what does not. So, these are some of the mistakes I have made personally and have also seen others make. It is by far not a comprehensive list but does provide some of the more important reasons and some potential solutions.

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So, You Are a Reliability Engineer Forced into Being a Facilitator

So, You Are a Reliability Engineer Forced into Being a Facilitator

Technical professionals are often asked to “lead” teams through the application of assessment tools such as failure modes and effects analysis (FMEA), Root Cause Analysis (RCM), and Reliability Block Diagrams. In some cases, you may be a department manager. In other cases, you are the subject matter expert. Sometimes senior management simply knows you are willing to do it.

The issue is not whether you are smart enough or the most personable engineer in the group. The problem is that you may have all the hard skills required to do the assessment, but you lack formal training in the soft skills. Most of us do the best we can. 

This article provides some insights for doing better rather than just being adequate.

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Opinions: Truth, Rumour or Belief

Opinions: Truth, Rumour or Belief

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

Humble, personal, professional, expert or even uninformed; opinions are just opinions when the facts aren’t fully known or understood.  Opinionators are merely stating their belief as to the what, why, when, where and the how something has happened and who was responsible, who is culpable and who has to do something. This belief is believed, at least by them, and, for the most part, they expect other people to believe it as well. 

Agreement brings harmony, collaboration and progress while disagreement brings confrontation, debate and procrastination while each party attempts to convert the other to their oftentimes sanctimonious viewpoint.

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Understanding First Article Inspection

Understanding First Article Inspection

For the seasoned manufacturing quality professional, First Article Inspection (FAI) is a familiar process performed after the first production run of a new or redesigned part. But for those outside of or newer to the quality profession, the requirements of FAI may provoke a lot of questions and uncertainty.

In short, FAI is the process of planning, conducting and reporting the verification of a production process. This verification “closes the loop” between the customer’s expectations — usually described on the part’s engineering drawing — and the actual output of the supplier’s process.

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The Future of Reliability Engineering

As we celebrate the new year, I am republishing an article I wrote last year, titled “The Future of Reliability Engineering,” as part of the Inside FMEA series. This article applies equally well to FMEA, as you will see.

Sometime in 2023, I will write an article titled “The Future of FMEA.” But, first, I want to hear from readers. Please write me with your ideas on what should be included in the future of FMEA. You can reach me at Carl.Carlson@EffectiveFMEAs.com

Wishing everyone on Accendo Reliability a happy and healthy new year, and best wishes for high reliability and effective FMEAs!

The Future of Reliability Engineering

by Carl S. Carlson

“Destiny is no matter of chance. It is a matter of choice. It is not a thing to be waited for, it is a thing to be achieved.” – William Jennings Bryan

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Systematic Evaluation Of Reactive Chemical Hazards

Systematic Evaluation Of Reactive Chemical Hazards

Evaluation of reactive chemical hazards can range from simple paper-based calculations to highly complex testing and modeling. This post is aimed at helping you formulate a systematic strategy for evaluating reactive chemical hazards in your facility.  I will divide the various approaches in three tiers – simple to complex.

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Earned Value Management Reduces Project Risk

Earned Value Management Reduces Project Risk

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

How does Earn Value Management (EVM) reduce project risk? To answer this question, you have to understand what EVM is.

WHAT IS EVM?

EVM is the tool used to measure progress against the PMB. (Performance Measurement Plan).  EVM identifies poorly performing WP (Work Packages) and problem trends early in the project allowing maximum time to identify the root cause of the problem and identify an action plan to fix the problem.

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How Humans Matter in Reliability

How Humans Matter in Reliability

In this episode, we talk about the more personal (or human) aspect of equipment Reliability. Who is responsible for Reliability? We know the answer is “everyone” – from top management to the experts who operate and maintain our machines. So it’s vital that we understand one another’s perspectives and responsibilities. We discuss how invisible obstacles can personally affect us – Comfort, the Prison of Perfection, Overwhelm, Our Thoughts, The Voices, and Fear. Fear can be the deadliest one of all. In this episode we discuss a simple – yet powerful technique – to manage fear. When we properly manage the obstacles, we free ourselves up to become more productive and effective equipment custodians.

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Sample vs. Population Estimates?

Sample vs. Population Estimates?

Rupert Miller said, “Surprisingly, no efficiency comparison of the sample distribution function with the mles (maximum likelihood estimators) appears to have been reported in the literature.” (Statistical “efficiency” measures how close an estimator’s sample variance is to its Cramer-Rao lower bound.) In “What Price Kaplan-Meier?” Miller compares the nonparametric Kaplan-Meier reliability estimator with mles for exponential, Weibull, and gamma distributions.

This report compares the bias, efficiency, and robustness of the Kaplan-Meier reliability estimator from grouped failure counts (grouped life data) with the nonparametric maximum likelihood reliability estimator from ships (periodic sales, installed base, cohorts, etc.) and returns (periodic complaints, failures, repairs, replacement, spares sales, etc.) counts, estimator vs. estimator and population vs. sample.

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