Software reliability and Hardware reliability are two distinct Concepts within the field of engineering each with its own unique characteristics and measurement challenges.
[Read more…]SW reliability
Agile EVM Based DOD Software Development Project WBS
Guest Post by John Ayers (first posted on CERM ® RISK INSIGHTS – reposted here with permission)
“Department of Defense (D0D) acquisition must improve program while working within budgetary constraints. The DoD community shows an interest in utilizing Agile methodologies, but struggles to reap Agile’s benefits. They encountered challenges including the historically built-up processes that enforce heavy-weight oversight, the outdated, manufacturing focused Work Breakdown Structure (WBS) provided in DoD Handbook: Work Breakdown Structures (WBS) for defense Material Items (MIL-STD-881C), and the inability of traditional waterfall-based process to accommodate iterative development.
[Read more…]Fundamentals of Vibration Measurement and Analysis Explained
Thanks to Peter Brown for this article.
1. Introduction:
The advent of the microprocessor has enormously advanced the process of vibration data acquisition and analysis in recent years. Measurement tasks that took hours only two decades ago can now be completed in minutes and better decisions made because of better data presentation.
However, the basic processes of measurement and analysis have remained essentially unchanged, just like the machines from which the vibration is measured. The results of the measurement and data analysis need to be compared with known standards or guidelines and decisions made as to whether the machine is acceptable for service or maintenance should be planned. Increasingly these processes are being handled electronically but we are still a long way from replacing the fundamental knowledge and experience of the vibration analyst.
In this article we will review the basic principles of vibration measurement and analysis in order to lay the foundation for capable fault diagnosis to be considered later.
[Read more…]Will you Accept a “No Brainer” Opportunity?
The “no brainer” opportunity
Imagine, 6 operational locations with a combined maintenance spend of $438 million and acceptable but mediocre performance. Production outputs ranged from 70% to 94% of nameplate values.
- The cost savings potential is $97 million.
- Improvement to nameplate levels adds upwards of $768 million in revenues.
- The spend to achieve that over 3 to 5 years was only $30 million.
That’s faster than the current mine permitting processes. Revenue was equivalent to adding a new mine at about 3% of the typical capital investment. Yes, this was a real customer in the mining industry with operations throughout North America.
[Read more…]The Importance of Proper Job Plans in CMMS and EAM Systems
By Paul Crocker CMRP CAMA, VIB1
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.
[Read more…]Condition Based Maintenance vs. Preventive Maintenance Tasks
Finding the Best with RCM
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…]Confidence Intervals (Part 3) for Proportion and Standard Deviation
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
Fundamentals of Managing an Outsourced (CM) Value Stream
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.
Markov Chain Analysis
Markov Chain Analysis and Eigenvector/Eigenvalue Problem: A Powerful Tool for Reliability Engineering
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.
[Read more…]5 Decisions Reliability Analysis Can Help With
Introduction to Reliability or Life Analysis
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.
[Read more…]How We Think About Reliability
How We Think About Reliability Is Important
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…]
How to Fit Data to a Distribution
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.
[Read more…]Maintenance Management Strategy by Physics of Failure Factors Analysis
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.
[Read more…]Disruption is Creating New Work Worlds
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…]Confidence Intervals for Mean ( part-2:) : Using t-distribution
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.
[Read more…]