Articles

Find all articles across all article series listed in reverse chronological order.

Statistical Software Problem?

When a system fails for the first failure in one mode at time t, this data is right censored data for other failure modes! How to estimate reliability functions for all failure modes from first failure data?

Google AI says, “’Competing risks’ refers to a statistical scenario where a subject can experience failure from multiple possible causes, but once one failure occurs, it prevents the observation of any other potential failures, essentially creating “multiple failure modes” that compete with each other to be the first event observed; this means analyzing the probability of a specific failure type needs to account for the possibility of other competing failures happening first.” “Use appropriate statistical methods: Employ statistical models specifically designed for competing risks analysis…”

[Read more…]

by Mike Sondalini Leave a Comment

The Science of Teams and Teamwork

There is something very powerful about working in teams. That power becomes evident when you look at teams as human structures built to deliver reliable outcomes. Managers who want higher reliability, top quality production and fewer problems need to understand why teams are so powerful and how to gain that power for themselves.

[Read more…]

by James Reyes-Picknell Leave a Comment

Proactive vs Reactive: which is better for your business?

Businesses often attempt to maximize profits for owners or shareholders by taking measures to reduce costs. A reactive approach to plant and equipment breakdowns is very costly, and it reduces outputs. By failing to do what it takes to become proactive, they take risks against the odds of frequent failure, high repair and downtime costs. A proactive approach is more productive, predictable and less expensive, as it relies on strategic maintenance.to increase equipment life and running times, reduce failure risk, and lower operating costs.

[Read more…]

by Nancy Regan Leave a Comment

RCM Analysis Success Starts w/Proper Scope Definition: 4 Key Factors

Hi everyone, I’m Nancy Regan, and in today’s video, we’re diving into the crucial role that scope definition plays in the success of Reliability Centered Maintenance (RCM) analysis. Proper planning is essential, and in this video, I’ll walk you through four key factors that demonstrate how the scope of your RCM analysis drives the entire planning process.

[Read more…]

by Hemant Urdhwareshe Leave a Comment

Hypothesis Testing Part-3: Two Sample t-test with tables and using Excel

Dear friends, we are happy to release our third video in our series on Hypothesis Testing! In this video, Hemant Urdhwareshe explains the application of Student’s t-test for comparison of two independent samples using tables of t-distribution and also using Microsoft Excel Add-ins. The concept is illustrated with an application example of comparing tire life of two makes.

[Read more…]

by Ray Harkins Leave a Comment

Understanding the Six Types of Measurement System Error

Our work as quality and reliability engineers, or as countless other technical positions across every industry, relies heavily on the instrumentation we use. Torque meters, tensile testers, micrometers, spectrometers and coordinate measuring machines provide critical data about the variation within the processes we design and maintain.

But these tools execute measurement processes which, like all processes, introduce variation into the results they generate. This fact – that every gage contributes variation to the values it reports – is the basis for Measurement Systems Analysis (MSA), a collection of statistical tools and approaches designed to isolate and quantify sources of measurement error.

[Read more…]

by Ramesh Gulati Leave a Comment

Are You A Hero or A Reliability Leader?

With Ramesh Gulati

The management and organization can create heroes and reliability leaders by their behavior. When an asset breaks down, some people in the workforce fix it quickly. We may celebrate their work as heroic, but another group of people fix things rapidly while finding and eliminating root causes. These proactive individuals are the real heroes, also known as Reliability Leaders. This webinar discusses the attributes of reliability leaders: the real heroes.

[Read more…]

by JD Solomon Leave a Comment

Facilitation & Collaboration: 10 Proven Tips For Asking Great Questions

“I can’t believe you asked him if he married a trophy wife,” my colleague stated. “Even more, I can’t believe he answered it without getting mad. Or that he told you so much about his first marriage and himself.”

“Well, the key was that I kept the questions short and followed where he took the conversation,” I replied. “On its own, the trophy wife is a bit over the top. But in the larger context, it flowed with everything he described and his comfort in discussing it with me.”

10 Tips for Better Questions in Business Environments

Effective communication is important in all relationships. The opening story was among business colleagues after a professional association meeting. While it is a bit personal, it reminds us that asking good questions – including in business environments – is personal.

[Read more…]

by Fred Schenkelberg 5 Comments

We Need to Try Harder to Avoid MTBF

Just back from the Reliability and Maintainability Symposium and not happy. While there are signs, a proudly worn button, regular mentions of progress and support, we still talk about reliability using MTBF too often. We need to avoid MTBF actively, no, I mean aggressively.

Let’s get the message out there concerning the folly of using MTBF as a surrogate to discuss reliability. We need to work relentlessly to avoid MTBF in all occasions.

Teaching reliability statistics does not require the teaching of MTBF.

Describing product reliability performance does not benefit by using MTBF.

Creating reliability predictions that create MTBF values doesn’t make sense in most if not all cases. [Read more…]

by Semion Gengrinovich 1 Comment

HALT or ALT ? Is it Only One Letter Differences?

HALT (Highly Accelerated Life Testing) is the foundation for the definition of HASS (Highly Accelerated Stress Screening) and HASA (Highly Accelerated Stress Audit).

HALT is primarily used to expose weaknesses in the design of a product by subjecting it to extreme environmental conditions such as temperature, vibration, and humidity, in order to identify and eliminate design flaws and weak points before the product is released to the market.

[Read more…]

by Greg Hutchins Leave a Comment

Electric Grid Risks

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

When the electricity grid fails, there is a risk of cascading impacts from what might seem to be a relatively minor event.

Having just watched a Electric Power video on this very topic, I feel obligated to inform the masses, what would happen if the power grid shut down?

If the power grid goes down, water and natural gas will also likely fail at some point, so planning is critical. Without a plan in place, most of us would be in bad shape with an extended grid outage.

[Read more…]

by Mike Sondalini Leave a Comment

How to Use SOPs to Achieve Zero Failure Operations

To get world class operation and profits your Asset Lifecycle Management System must prevent every opportunity for defect-creation in all life cycle phases, for all your operating equipment

Every physical asset has a lifecycle starting at conception through to its eventual disposal and site remediation. In each phase of the lifecycle errors can occur that cause defects within the asset. In operations with hundreds of assets there easily can be tens-of-thousands of defects. Each defect is a risk that eventually contributes to breakdowns, losses, wastes, safety incidents during operation, and shortens the asset’s service lifetime. Eliminating thousands of defects and risks forever is what Plant Wellness Way EAM does for its users.

[Read more…]

by Nancy Regan Leave a Comment

Defining Your RCM Analysis Scope to Achieve the Results You Need

Join me, Nancy Regan, as I guide you through the process of effectively defining the scope of your Reliability Centered Maintenance (RCM) analysis to ensure you achieve your desired analysis goals. In this video, I’ll illustrate the importance of tailoring the RCM analysis scope using a practical example of a Plant Air system. Key Takeaways: • Understanding Scope: Learn how to avoid common pitfalls by appropriately narrowing down your analysis to a manageable size. • Adapting to Environments: Gain insights into how identical equipment can behave differently in varied operational environments and why specifying your analysis scope is crucial for clarity and effectiveness. • Goal-Oriented Analysis: Understand how the goals of your RCM analysis, such as developing a proactive maintenance plan, dictate the scope and focus of your analysis. What’s Next?: Stay tuned for tomorrow’s video where I delve deeper into why accurately identifying the scope of analysis is foundational to successful RCM analysis planning. Subscribe and hit the bell icon to follow along with the “100 Days of Reliability” series and enhance your Maintenance and Reliability knowledge with expert insights. Thank you for watching! Remember, the success of your RCM efforts starts with the right scope!

[Read more…]

by Hemant Urdhwareshe Leave a Comment

Hypothesis Testing Part-2: One Sample t-test, t-distribution, Degrees of Freedom and P-Value

Dear friends, we are happy to release this second video on Hypothesis Testing! In this video, Hemant Urdhwareshe explains One Sample t-test along with illustrations of Student’s t-distribution. Hemant has also explained the concept of degrees of freedom and p-value in this video.

We recommend viewers to watch Hypothesis Testing, Part-1 video before this video.

We are sure, you will find this useful!

[Read more…]

by Steven Wachs Leave a Comment

Sample Sizes for Hypothesis Testing

As an industrial statistics consultant for the past 25 years, I have frequently fielded questions related to sample size determination. Unfortunately, I have encountered many instances where simple rules of thumb were used for any purpose (like always use 30). Sample size guidance really depends on what the goal of the study is, the type of data we are dealing with, what statistical method we are using and some other factors as well. Common activities which typically require sample size determination include:

Hypothesis Testing (including Equivalence Testing)
Estimation of statistics like means, standard deviations, proportions
Calculation of Tolerance Intervals (range of data a process uses)
Designed Experiments (number of replicates)
Statistical Process Control Charts (e.g. X-bar charts)
Acceptance Sampling (to disposition lots or batches of raw materials or finished products)
Reliability Testing to estimate Reliability performance
Reliability Testing to demonstrate Reliability performance

All these applications require different assumptions and calculations to determine an appropriate sample size. In this article, we focus on Sample Size determination for Hypothesis Testing. It is assumed that the reader is already familiar with Hypothesis Testing.

[Read more…]