Your Reliability Engineering Professional Development Site
Find all articles across all article series listed in reverse chronological order.
In today’s industrial environment, the efficiency and reliability of maintenance operations are crucial. This is where Computerized Maintenance Management Systems (CMMS) and Enterprise Asset Management (EAM) systems come into play. These systems are designed to manage the maintenance function by tracking maintenance work, parts used, failure codes, and more.
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Hi everyone, I’m Nancy Regan, coming to you from the Watermelon Festival in Russellville, Alabama! In today’s video, I talk about how Reliability Centered Maintenance (RCM) can help you find the “sweet spot” when choosing proactive maintenance tasks for your equipment.
Just like every watermelon has a sweet spot, RCM helps you pinpoint the best maintenance task for each Failure Mode. Using a simple example like “oil degrades due to normal use,” I explain how RCM guides you to decide between different options, such as Scheduled Replacements or Condition Based Maintenance. By answering the RCM questions, you can figure out which task is the most cost-effective or reduces the risk of failure to an acceptable level.
[Read more…]Dear friends, We are happy to release this third video in our series on Confidence Intervals! In this video, Hemant Urdhwareshe has explained how to determine confidence intervals for population proportion and standard deviation with day-today application examples! Hemant has also illustrated use of templates for quick calculation!
Links to other related videos:
Confidence Interval (Part-1) for Mean (Sigma Known)
Confidence Interval (Part-2) for Mean (Sigma unknown)
Chi-square Test of One Variance
This article will cover the management of a contract manufacturer (CM) value stream from the perspective of a company that has outsourced the manufacturing of its product. A typical CM model is most likely “turn-key” such that the “Company” purchases the only finished goods from the CM.
Part/component purchases are a shared responsibility between the company and CM. Company-controlled suppliers have negotiated pricing and purchased orders may be placed by the company or the CM for long-lead and specialty items.
Ultimately, the liability for part/component inventory rests on the company. For this reason, minimizing inventory, maximizing inventory turns, and value stream flexibility are some major objectives of managing a CM.
In reliability engineering, predicting system behavior over time is crucial for maintenance planning and risk assessment. One powerful mathematical tool for this analysis is Markov Chain modelling. In this article, I’ll demonstrate how Markov Chains can predict device reliability using a real-world example: battery reliability in reliability testing facilities.
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Reliability Analysis or Life Analysis is a process where asset records are used to build a statistical model for the asset. The model will in turn provide information of its future performance. It becomes an indispensable tool for asset managers in terms of making life cycle decisions with regards to the asset preservation and eventually replacement. Let alone the safety of employees. Typically, though not necessarily always, those records are obtained from the Computer Maintenance Management System (CMMS).
The basis of the model is a statistical distribution. An example of the process is illustrated in Diagram 1 where a number of “n” centrifugal pumps are run on a test bench until they fail. Each time interval to failure is recorded and once all the failure records are collected, a normalized frequency graph can be constructed. This frequency graph helps define the statistical distribution that best represents the life cycle of a typical component in the population. Using specific mathematical transformations applied to the distribution, the probability of failure after a defined mission time can be derived. And much more information as we will discover in this article.
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Getting on an airplane we think about the very low probability of failure during the flight duration. This is how we think about reliability.
When buying a car we think about if the vehicle will leave us stranded along a deserted stretch of highway. When buy light bulbs for the hard to reach fixtures we consider paying a bit more to avoid having to drag out the ladder as often.
When we consider reliability as a customer does, we think about the possibility of failure over some duration.
And, we really don’t like it when something fails sooner than expected (or upon installation). [Read more…]
Understanding the different types of data and their respective uses is critical for product development, testing, and analysis. Each type of data plays a role in ensuring that products meet quality standards and fulfill user needs. As a mechanical engineer with a focus on R&D testing and data analysis, you would likely encounter and utilize these various data types throughout the product development and validation process.
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The Physics of Failure Factors Analysis for selecting maintenance strategy is a one-person exercise that identifies all ways a component can physically fail. Equally important to its simplicity is its ability to select the most effective life cycle strategies for maximising reliability. Another powerful business advantage is the failure-addressing solutions arrived at are universal solutions that apply to every other identical component, whatever equipment it is in. Do a Physics of Failure Factors Analysis for one part and you do it for all identical parts for the life of your operation. It is a highly accurate and cost-effective maintenance strategy selection methodology.
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There are lots of lessons to learn from Amazon. Never stop innovating or questioning the fundamentals of your business. Disrupt yourself before others do.
Brad Stone – Journalist & Author
Consulting firms, academics, and consultants are developing models for the Future of Work. Price Waterhouse Coopers (PwC) developed a scenario called the Future of Work: A Journey to 2022. The premise of the study is: “disruptive innovations are creating new industries and business models, and destroying old ones.”[i] PwC outlined three distinct worlds of work: Blue, Green, and Orange.
[Read more…]Dear friends, we are happy to release this Part-2 of our videos on Confidence Intervals. In this video, Hemant Urdhwareshe explains how to estimate confidence interval of population mean when population standard deviation sigma is not known In such cases, we need to use Student’s t-distribution instead of normal distribution and Z-Score.
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Hi everyone, I’m Nancy Regan, coming to you from The Watermelon Festival in Russellville, Alabama! In today’s video, I share one of the most common mistakes organizations make when it comes to Reliability Centered Maintenance (RCM)—and why this often leads to failed analyses.
Using a simple analogy of growing watermelons, I explain how RCM can go wrong when the right people aren’t involved. Just like watermelons need the right conditions to grow, RCM needs experienced facilitators and equipment experts to ensure the process succeeds.
[Read more…]In this final article of the series, we will cover the right leg of the “V” diagram which illustrates the process of verifying and integrating hardware into the system.
Defining a proper product reliability goal is a critical step in ensuring that a product meets customer expectations and performs adequately throughout its intended lifespan. This also involves a careful balance between the required level of reliability and the associated costs and complexities of achieving that reliability.
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MTBF is not reliability. Attaining a specific MTBF does not mean your product is reliable. MTBF use may be the culprit.
Therefore, working to achieve a MTBF value may actually be preventing you from creating a product that mets your customer’s reliability performance expectations.
Actively working to achieve MTBF using the common tools around MTBF may be taking you and your team down the wrong rabbit hole. You may be working to reduce the reliability of your products rather than improving them.
Let’s take a look at a couple of ways the pursuit of MTBF is harmful to your product’s reliability potential and contrary to your customer’s expectations. [Read more…]