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Key Teaching Principle # 7: Clarity

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.

Speak with Clarity and Confidence

It isn’t about the words you say. It’s about the energetic message you send. Pete Carroll [Read more…]

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Opportunities for Maintenance and Operations: Alarms

George will be discussing basic opportunities for Maintenance and Operations. This is an 8 part video series that covers things such as eliminating nuisance alarms, looking into event rates, and how we develop PM Routes. This first video covers Alarms. What does opportunity look like from an alarm perspective? In most plants, it’s likely you have some type of building automation. Systems and Alarms can go through what is called a Pareto Analysis. Watch to learn more!

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Weibull Distribution Part-1

Weibull Distribution Part-1

This is the first of our two videos on Weibull Distribution. In this video, Hemant Urdhwareshe explains the basic concepts of Weibull Distribution, its cumulative and probability functions, hazard function and effect of shape parameter on these functions. Hemant also explains the related mathematical treatment briefly. The concepts are explained with an application case study of tires to calculate reliability within warranty period. The video additionally explains calculating probability of failure and reliability using Microsoft Excel functions. The videos would be useful to those who want to learn applicability of Weibull Distribution to estimate reliability and to those who wish to take ASQ CRE, CQE and CMBB certification exams.

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Dependency Concept in RAM Analysis

Dependency Concept in RAM Analysis

Assets or components in an operation can be dependent on each other. The network of equipment contributing to the operation output is complex and intricate. A RAM model helps account for the complexities including dependencies.

The fundamental purpose of Reliability, Availability, and Maintainability (RAM) modeling is quantifying system performance, typically in a future interval of time. A system is a collection of items whose coordinated operation leads to the output, generally a production value. The collection of items includes subsystems, components, software, human operations, etc. For example, an automobile is a system. Its sub-components being the drivetrain, engine, gearbox, etc. In RAM models, it is crucial to account for relationships or dependencies between items. This helps determine the final output of the system. In various industries, RAM models have proven to be effective as cost avoidance or decision-making tools, as well as their ability to confirm or counter stated assumptions by internal stakeholders.

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How About Weibull Instead of MTBF?

How About Weibull Instead of MTBF?

What About Weibull? Can I Use it Instead of MTBF?

This was a follow-up question in a recent discussion with Alaa concerning using a metric other than MTBF.

The term ‘Weibull’ in some ways has become a synonym for reliability. Weibull analysis = life data (or reliability) analysis. The Weibull distribution has the capability to describe a changing failure rate, which is lacking when using just MTBF. Yet, is it suitable to use ‘Weibull’ as a metric? [Read more…]

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The Link Between Agile and Agility

The Link Between Agile and Agility

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

In the previous article in this series, we discussed the difference between Agile and business agility and how Agile 2 addresses some of the omissions and failings of traditional Agile.  Both Agile and Agile 2 focus on accelerating digital development; however, the benefits of any Agile approach can be obviated if it is not implemented within an agile management structure.  Addressing execution issues, as Agile 2 does, will not be sufficient by itself to get you where you need to go. 

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Design for Reliability by using Design-out Maintenance to get High Reliability Equipment

Design for Reliability by using Design-out Maintenance to get High Reliability Equipment

Design-out maintenance is a root cause failure elimination category where the solution is to design for reliability and intentionally create highly reliable equipment through an engineering design change.

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I am a design engineer and am considering plant improvement as a more proactive activity for our department. Being in design I am interested in design-out maintenance solutions and the role they play in maintenance cost reduction. Particularly where design out solutions are used for failure elimination.

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Hazard Rate and Related Concepts in Reliability Engineering

Hazard Rate and Related Concepts in Reliability Engineering

In this video, Hemant Urdhwareshe explains concept of hazard rate which is very important in reliability engineering and also in insurance business! The video will be useful to all those who want to understand this basic concept. It will be also be useful to all those who wish to prepare for ASQ Certified Reliability Engineer (CRE) exam.

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FINESSE Fishbone: The F Stands for Frame

FINESSE Fishbone: The F Stands for Frame

The F in the FINESSE fishbone diagram stands for Frame. Effective communication requires systems thinking. That’s the good news for most technical professionals – you do not need to be perfect but only need the cause-and-effect bones of FINESSE to work together. These are three tips to help you develop the frame.

Use “The Greatest Fear”

Focusing on your greatest fear is an alternative way to frame a problem. Framing the problem is also the first step in effective communication using the FINESSE approach for problems with high levels of complexity and uncertainty. [Read more…]

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Use Lognormal Distribution

Use Lognormal Distribution

The lognormal distribution has two parameters, μ and σ. These are not the same as mean and standard deviation, which is the subject of another post, yet they describe the distribution, including the reliability function.

$$ \displaystyle R(t)=1-\Phi \left( \frac{\ln (t)-\mu }{\sigma } \right)$$

Where Φ is the standard normal cumulative distribution function, and t is time. [Read more…]

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Great Communications are Essential for Business Prosperity

Great Communications are Essential for Business Prosperity

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

The last few years have proven the risk landscape is dynamic and evolving. And while an organization focuses on responding to one crisis, another is almost always lurking in the shadows—from COVID variants and severe weather to supply chain, and civil unrest and cybercrime. In fact, you could even find yourself in the dark – literally.

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Poisson Distribution and its Application using Formula, Tables and Excel

Poisson Distribution and its Application using Formula, Tables and Excel

In this video, Hemant Urdhwareshe explains applicability of Poisson Distribution along with its application examples. Solutions to application examples are illustrated using basic formula, tables of Poisson Distribution and also Microsoft Excel. Hemant also explains the mean and standard deviation of Poisson Distribution. The video will be useful to all those who want to learn basics of Poisson Distribution and prepare for ASQ Certification Exams such as Certified Quality Engineer (CQE), Certified Reliability Engineer (CRE), Six Sigma Black or Green Belt (CSSBB or CSSGB).

[Read more…]