Your Reliability Engineering Professional Development Site
All articles listed in reverse chronological order.
In times that promise to be a financial challenge for many corporations, we must make decisions as to where to invest our scarce dollars and where to cut from our current operations. When faced with these decisions, we must be realistic and pragmatic about how short-term decisions impact our long-term goals. Yes, when times are hard, how well positioned will we be when the economy picks up (and keep the faith, it will pick up)? [Read more…]
Frac plugs create a seal with the inner diameter of the casing. With the frac ball on seat in the frac plug, a check valve is formed in the casing which resists fracturing pressures up to 15,000 psi. Composite frac plugs use substantially composite components and rubber seals. Degradable frac plugs use components manufactured from magnesium (Mg) alloys. [Read more…]
A common refrain from managers and engineers alike (as it relates to making or maintaining reliable products) is:
How do we know if we are there yet?
This makes reliability engineering sound like driving a car, sanding a piece of wood, mowing the lawn, or any other endeavour where efforts perfectly align with progress.
This doesn’t work for reliability. Reliability can be easy to achieve, but it needs to be thought about in a different way. And when you do, everything becomes easier. [Read more…]
Performing a PM Optimization is not always as simple as it sounds. Often a Maintenance Planner will assemble a team of technicians to ask what is value-added and what is missing from a PM Routine. While these may be good questions to ask before diving into an analysis, or after an analysis, it does not base the answers on data. Basing the PM Routine on data, not intuition is critical to the long-term success of any organization.
To perform a PM Optimization, there are three main types of analysis to focus on the effectiveness of any PM Routine. The specific analysis used will depend on how mature (or effective) the current PM Routine is, and on the specific type of failures that the PM Routine is trying to address.
If the current PM routine was not developed utilizing an acceptable tool such as Reliability Centered Maintenance, Failure Mode Effect Analysis, or Maintenance Task Analysis, then this is the first step to performing a PM Optimization. By utilizing Review RCM, or an FMEA, the organization can begin to document and analyze the current failure modes experienced with a specific piece of equipment. This analysis will identify if the current tasks are effective for the type of failure (i.e. wear out or random failure).
At the completion of the Review RCM analysis, a documented equipment strategy will be available to ensure that the right maintenance is being performed for the specific type of failure mode. At this point, the organization can implement changes to their PM program and begin to experience an improvement in the effectiveness of their PM Program.
But what if the PM Routine was developed utilizing an accepted tool? Then there are two other types of analysis that should be utilized to analysis the failure data and make data-driven improvements to the PM Routine.
A Weibull analysis is a common statistical analysis tool used in maintenance and reliability. The Weibull analysis is used for Non-Repairable Components, meaning that it is used for parts that are discarded after failure.
To use a Weibull analysis, begin by plotting the life data. A Beta (or slope) of the plot will provide information as to whether the failure is related to a wear-out failure mode, a premature failure mode or a random failure;
While quite effective with non-repairable components, the Weibull analysis can only be used with a single failure mode. If multiple failure modes are included in the life data, the Beta will not be correct.
With the Beta determined, the type of maintenance being performed can be reviewed to determine if it is in line with the type of failure being observed, i.e. random, or age related. If the maintenance activity is replacing a component every 300 days and the Beta value is 1, then the right type of maintenance is not being performed and an on condition task should be established.
Lastly, the characteristic life (n) for an age-related failure will be provided as part of the Weibull analysis. This can be used to assist in determining the appropriate frequency of the maintenance activity.
Now, if the component being maintained is a repairable component, a Weibull analysis is not the right tool to use. This is where a Mean Cumulative Function Plot comes into play. This is a plot of time in hours versus the count of failures to date.
By plotting the time in hours versus the count of failures, you can begin to see how long components are lasting. Also, you can perform an analysis on the data which will indicate the slope of the data;
Based on this line, the type and effectiveness of the maintenance activity can be evaluated. As with the Weibull analysis, the data will allow the organization to see what failure modes are occurring when. With this information, the maintenance activity and frequency can be reviewed. A word of caution, do not take the average of the life data. Look at the plot and determine when the maintenance activity should be performed based on the probability of preventing the failure.
Armed with this three analysis, any organization can effectively perform a PM Optimization focused on the effectiveness of the maintenance activities. However, this is only the first part of a PM Optimization process. The cost/benefit must be calculated to determine if the maintenance activity is worth doing. If it has been determined that the PM Routine is worth doing, then the PM routine needs to be analyzed to perform it in the most efficient way.
Do you have a structured approach to your PM Optimization? Do you use a rule of thumb for your reviews? What is preventing you from using data to perform your PM Optimization?
Remember, to find success; you must first solve the problem, then achieve the implementation of the solution, and finally sustain winning results.
I’m James Kovacevic
Eruditio, LLC
Where Education Meets Application
Follow @EruditioLLC
References;
The Central Artery/Tunnel Project, known as the Big Dig in Boston, originally was planned to take 10 years to complete for a budget of $2.5B. It actually took 30 years and cost $14.8 B. The traditional project framework used was inadequate for a long duration project. A new project framework, I call Adaptive Rolling Wave, is needed. It is a combination of the Adaptive Project and Rolling Wave framework, that is more suited for a long duration project because it breaks down the project into a number of smaller projects. [Read more…]
A visit to Quincy Market in Boston clears up a big misconception about RCM. It isn’t feasible to do RCM on all your equipment. Here’s why… [Read more…]
Setting up industrial operations is part of the capital expenditure a business has to undertake. Businesses now analyze the lifetime cost of any capital expenditure before making a decision. This includes the inventory cost, labor expenses, maintenance costs, cost incurred due to expected downtime, and expenses for upgrades. This tilts the decision in favor of options that provide long-term machine reliability and reduced maintenance.
I often talk to engineers who have just been told that they are now a ‘reliability guy or girl’ for their organization. The CEO or perhaps a director decides that reliability is now important, so a group of poor unfortunates are hastily and collectively anointed as ‘the’ reliability program. Is this familiar?
Sometimes this works. Sometimes these rebranded ‘reliability guys and girls’ create amazing programs that [Read more…]
Does this paradigm apply at your workplace?:
“We NEVER seem to have the time and budget to do things right, but we ALWAYS seem to have the time and budget to do them again!”
While this article was written for manufacturing many years ago, is it any less applicable today, in any industry?
In the petroleum, natural gas and petrochemical industries, great attention is being paid to safety, reliability, and maintainability of equipment. This is true in any industry and as such the learnings and information found within ISO 14224 can be applied to any industry. [Read more…]
In 2014, at an IMEC conference organized by the University of Toronto, Art Rice of Maintenance Technology Magazine said that in many cases “Lean is a form of Anorexia”. He was right then, and he is still right today.
When I heard him, I realized that in many cases where I’ve seen attempts at “lean manufacturing” the lean really means “understaffed”. In those cases some of the lean manufacturing tools have been implemented, often with the help of outside expert help but lean results haven’t occurred. The introduction of “lean” in those companies was yet another attempt to cut costs without any deep thought as to what caused the high costs before introducing “lean”. [Read more…]
Working From Home (WFH)…just one of the things that the “New Normal” will bring according to a few voices from the populations of various workforces who have contributed to economies during lockdowns. People seem to have enjoyed the utopia of ‘flexible’ working hours with a freedom to work when they want, attending virtual meetings and collaborating in on-line virtual offices. [Read more…]
One of the most common questions I get from students in my Process Capability Class is, how can I use the capability index from my process to approximate a defect level for my process? [Read more…]
I recently held a lunch and learn about infographics. The recorded session is below. In our work as engineers, we often spend a great deal of time extracting amazing information from complex data sets only to find no clear way to get our message to those who need it which can include leadership, peers, or even the customer.
Changing how we present information can be the difference between driving change and simply being a slide in a weekly status meeting that solicits the response “next.”
What if you knew all the possible outcomes for your product’s reliability performance due to component variations, for example? What if you knew the future with enough certainty to make a difference?
Building on brainstorming, what-if analysis involved using models or prototypes that allow you to change something and see how it alters the output or performance. What if we change this support bracket from iron to aluminum? What if we swap out this 100 ohm resistor for a 200 ohm one?
As a curious engineer you could spend many, many hours conducting what-if based experiments, so there is a bit more to this idea then just a random walk of changes. [Read more…]