I have a service that regularly monitors my home for termites. Using RCM, let’s determine if this Condition Based Maintenance task is both technically appropriate and worth doing.
[Read more…]“Gnaw” on this…served with a side of RCM…
on Maintenance Reliability
A listing in reverse chronological order of these article series:
- Usman Mustafa Syed — Aasan Asset Management series
- Arun Gowtham — AI & Predictive Maintenance series
- Miguel Pengel — Asset Management in the Mining Industry series
- Bryan Christiansen — CMMS and Reliability series
- James Reyes-Picknell — Conscious Asset series
- Alex Williams — EAM & CMMS series
- Nancy Regan — Everday RCM series
- Karl Burnett — History of Maintenance Management series
- Mike Sondalini — Life Cycle Asset Management series
- James Kovacevic — Maintenance and Reliability series
- Mike Sondalini — Maintenance Management series
- Mike Sondalini — Plant Maintenance series
- Andrew Kelleher — Process Plant Reliability Engineering series
- George Williams and Joe Anderson — The ReliabilityXperience series
- Doug Plucknette — RCM Blitz series
- Robert Kalwarowsky — Rob's Reliability Project series
- Gina Tabasso — The Intelligent Transformer Blog series
- Tor Idhammar — The People Side of Maintenance series
- André-Michel Ferrari — The Reliability Mindset series
The Evolution of Maintenance Practices
- What is Maintenance?
- An Historical Perspective of Maintenance
- Equipment Reliability
- Reliability and Maintenance Strategy
- The Ongoing Evolution
- Effective Maintenance – DuPont Maintenance Study Results
- Making the Transition from Reactive to Strategic
- Discussion
1. What is Maintenance?
A definition: Maintenance describes the management, control, execution and quality of those activities which will reasonably ensure that design levels of availability and performance of assets are achieved in order to meet business objectives. [Read more…]
Opportunities for Maintenance and Operations: Design Rates
Today we are going to look at Design Rates. Often times our equipment are not running at their designed rate. Most of which are operational issues. For example, we tend to slow down a line, to present less problems, but it lowers the target rate. How do we identify an actual opportunity?
[Read more…]Interpretation of Moubray’s Failure Patterns
Failure Patterns according to Moubray
In his book Reliability Centered Maintenance1, John Moubray highlights 6 patterns of failure. However, one needs to be careful about how those patterns are interpreted and used. Or misused. These 6 failure patterns are as follows:
- A: Bathtub Pattern
- B: Age Related or Wear Out Pattern
- C: Fatigue Pattern
- D: Initial Break-in Pattern
- E: Random Pattern
- F: Infant Mortality Pattern
Plot a Distribution Curve of Maintenance KPIs
MAKE USE OF A PROBABILITY DISTRIBUTION CURVE OF MAINTENANCE KPIS TO SHOW WHETHER YOUR MAINTENANCE PERFORMANCE IMPROVEMENT EFFORTS ARE WORKING. A KPI PROBABILITY DISTRIBUTION CURVE GIVES NEW INSIGHTS INTO YOUR MAINTENANCE PERFORMANCE.
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Using a distribution curve of maintenance KPIs as a new maintenance performance measure was what we recommended to this Maintenance Manager.
[Read more…]A Biohazard and Achieving Goals
Advice to Managers on Getting Most Value from Workforce Training
The purpose of training your people is to develop capabilities the business needs and to add value to your people so they feel that they have greater worth. But the most important benefit of training is often lost because managers do not get their newly trained people to improve the system of work with their better knowledge and skills.
Everyone needs training to reach their highest potential. Training introduces new ideas and new ways that make us more effective people. There is one vital issue managers need to keep in mind about training if you want to get the greatest returns from the investment in time, money and commitment. Only training put to use returns value and only training of value is of use.
[Read more…]Opportunities for Maintenance and Operations: No Part Replaced
This informative video provides valuable insights into how we respond to operations and help them improve their processes. By pulling data out of the CMMS, we can identify areas of opportunity and provide recommendations for improvement.
For example, by analyzing the data, we can see where operators may need training, or where improvements can be made in the incoming raw material process. Our goal is to provide practical, actionable advice that can help you maximize your resources and achieve success in your manufacturing facility.
[Read more…]Building a PF Curve Using Life Analysis Concepts
Definition of a PF Curve
A PF curve is a graphical tool used in the field of maintenance and reliability. It essentially illustrates a component’s health degradation over its lifetime. As well as a visual guide on when to conduct appropriate action to minimizes operational risks related to unplanned failures. It is essentially a planning tool.
[Read more…]Why do Machines and Equipment Continue to Fail?
This white paper will teach you how to solve your plant and equipment reliability problems and improve your current plant and equipment reliability up to magnificent performance.
Since the mid-1980’s we have known exactly how to guarantee incredible equipment reliability. Failure-free machinery and equipment is totally achievable (in fact it is remarkably straightforward to do). We have all the answer—we know all the science; we know all the engineering; all the necessary information is readily available. The research has long been completed. The correct solutions for magnificent reliability are practical and quite doable. The problem that remains, is that though we know exactly what needs to be done to get magnificently reliable machines, we cannot get companies to do it right. The limitation to achieving magnificent reliability is not technical. The limitation now seems to be organisational, cultural, and human factors related.
[Read more…]TVs Are “Risky” Business
When it comes to managing risk, there are three elements to consider and RCM can help you define all three. Watch as I manage risk and change consequences all at once!
- What happens when the failure occurs?
- How likely is it that the failure would occur?
- Is the risk tolerable?
How Management Decisions Make or Break Plant Uptime
When you run machines above design rates that decision goes against all that we know about creating high plant uptime and outstanding equipment reliability—in fatigue situations 10% additional stress will cost you ten breakdowns.
The dominate factor in machine life and production plant uptime is the stress in your machines’ working parts. The stress developed in a part’s material of construction microstructure is directly linked to the force applied to it. It does not matter where the force comes from or why it is applied, once the stress in your parts go beyond their microstructure limits your machines fail. If you want to run at high production rates first ensure that your working parts cannot become overstressed.
[Read more…]Opportunities for Maintenance and Operations: PM Route
We are back with our 4th installment in the Opportunities for Maintenance and Operations series! We have discussed alarms, rework, and event rates. Today we talk about PM Routes. What can a PM Route do if our CMMS system has the ability to manage them? How does one take advantage? Watch the video and find out.
[Read more…]Using a Weibull Distribution to model Production Output
In probability theory and statistics, the Weibull distribution is a continuous probability distribution. It models a broad range of random variables. Largely in the nature of a time to failure or time between events. It addresses mechanical or structural failures in the field of Reliability Engineering. By nature, the Weibull distribution provides a lot of information such as aging characteristics or expected asset lifetime. One of its most common outputs is the Bathtub Curve.
[Read more…]Preventing Failure Using Physics of Failure Science
Physics-of-Failure warns us to keep the sum of all static and cyclic loads on a part’s microstructure below its fatigue stress limit.
The image below shows two example metal fatigue limit failure curves. These curves were determined based on controlled laboratory experiments. These experiments use a machine with a fixed load to test the selected piece’s microstructure stress levels. Curve A shows that at a high stress level, close to the Ultimate Tensile Strength of steel, the test piece failed after 10,000 cycles. As the fatigue stress level is reduced, the test piece lasts longer. When the imposed stress is limited to around 50% of the UTS, the cycles to failure had no measurable limit. On the other hand, Curve B shows that at all levels of fatigue stress the component would eventually fail. However, the same outcome can be seen, that as stress reduces the service lifetime before failure increases.
[Read more…]