|
“Connecting Reliability to EAM”
By Ricky Smith, CMRP
Ivara Corporation
Most companies that I have visited claim to have no link between
equipment reliability and their EAM system. I believe it is very
important to link the two. The goal of those involved in equipment
reliability should be asset performance, and EAM’s were not built to
help with that objective. Despite the fact that every good EAM
provides very valuable capabilities, and virtually every large plant
has implemented an EAM, plants continue to fall apart. I believe
that most plant maintenance and operations groups have a huge
opportunity to make a much bigger contribution to the bottom line,
and the way to do it is to link their reliability efforts with their
EAM system.
EAM’s Play a Vital Role
EAM’s do not reduce failures or increase reliability by themselves.
However, they do play a vital role in optimizing the efficiency of
work execution. An EAM automates the writing of a work request, aids
in planning and scheduling work, tracks work history and records all
costs. EAM’s however have not been designed to improve plant
performance, only the efficiency of the maintenance work force and
records keeping.
Improved Equipment Reliability Drives Huge Benefits
Improving plant performance by managing the reliability of the
assets leads to significant business benefits by:
-
increasing production output
-
decreasing cost
-
reducing need for capital replacement
-
maximizing competitiveness and protecting jobs
Many Approaches to Linking Reliability and EAM Have Been Tried
Many companies have tried unsuccessfully a variety of approaches to
link reliability and their EAM? One common approach is to integrate
a Reliability Centered Maintenance (RCM) toolkit to the EAM. This
approach performs a one-time copy of the RCM’s output - proactive
tasks - into the EAM. While this data transfer function can help to
avoid the key stroking of loading the RCM tasks into the EAM, it
fails to deliver significant value because it’s not implementing the
results of the RCM analysis. Once you load a bunch of RCM tasks
into an EAM, you’re faced with the impossible task of managing the
enormous volume of the equipment health data that results from the
RCM, using a tool (EAM) that provides no such capability
whatsoever. Imagine keying a condition reading into the text fields
of a work order. How would you ever trend or analyze this kind of
potentially valuable information? In fact, some EAM’s are so
user-vicious that you’d soon find users unwilling to even key the
data into the work order text fields in the first place.
Another approach that has been receiving attention lately is the
idea that if we could extract failure data from our EAM, we could do
a better job of reliability. The theory goes something like this;
if we could use a software tool to pull the history of an asset’s
failure out of EAM, and if we did some really sophisticated math to
plot these historical frequencies and project the future failure
timing, we’d be able to implement perfectly timed Preventive
Maintenance (PM) jobs that would result in improved reliability. In
my view, this theory is one of the most damaging ideas out there.
Don’t be intoxicated by the sophisticated math and graphs. We now
know that the majority of failures are not related to time (read any
book on RCM), and that we’re already spending way too much effort
already on time-based PM’s. To get really sophisticated about
calculating PM frequencies using failure history is an admission
that we’ve given up on improving reliability. And when was the last
time you saw an EAM that contained useable failure history anyway?
A somewhat better approach that I have seen, that I think has
potential merit if done properly, is to invest in linking predictive
technology, such as thermography, oil analysis and vibration
analysis to the EAM. I say they have potential because I really
believe that for certain failure modes, we need these tools. The
pitfall is that if you link these tools, or other sources of
electronic condition data such as PLC’s, directly to an EAM, you end
up putting good data into a tool that was not designed to help us
make asset health based decisions. The right way to leverage these
predictive investments is to link to the EAM indirectly – through a
tool that will manage the data.
The
Right Way
to Link Reliability to an EAM
The right way to create a link between reliability and the EAM is to
start by recognizing that reliability is not a software challenge –
it’s a people challenge. We need to change attitudes beliefs and
culture. We’re doing the wrong work to maintain our assets so the
change process should be drive by a proactive reliability process.
The EAM and the other systems that we use should play a support role
– supporting the execution of the process. Below is a simple
example of a proactive asset reliability process.
Figure 1: A typical proactive asset reliability
process
The typical EAM does a nice job of supporting the blue box in the
process – it helps us to be more efficient in planning, scheduling
executing and following up on work, than we would be if we did all
of those things manually. EAM’s can be a good investment for this
purpose. However, the EAM must be seen as a piece of the technology
support for maintenance; not the entire “maintenance system”. What
is needed is technology to support the rest of the process, in order
to monitor asset health and drive work based on asset health data.
Research has proven that time-based PM’s apply to less than 20% of
failure modes. We must monitor asset health and make decisions based
on health data and degradation of asset health prior to failure.
Think about assets in your plant whose health is degrading but has
not failed yet. Wouldn’t it be great if you would to be able to
monitor the health of your assets? Then instead of reacting to
equipment failures (whether partial or total functional failures)
you will know far in advance about equipment failure and be able to
make sound decisions based on asset health data. You would have
options such as:
·
Scheduling “maintenance down day” as close to the failure as
possible, not too early and not too late.
·
Re-scheduling production if needed instead of production reacting to
the failure and possibly upsets customers especially if your
operation produces product “just-in-time”.
·
Identify the “right maintenance work at the right time”
Today, most progressive plants have all sorts of raw data that could
help to create a picture of asset health. They have process control
tools, they collect inspection data, they use various forms of Work
Identification (work ID) such as RCM an others, and they have
invested in predictive tools. The problem is in figuring out how to
link all of this data to the EAM. See Figure 2.
Figure
2: How do we link asset health data to an EAM?
The right way to link your reliability efforts with your EAM is use
technology in between the data sources and the EAM – a reliability
application that can manage all of the data, trend it over time, and
highlight equipment degradation before the failure occurs. By
“reliability software” I mean an application that will:
·
Prioritize all assets in terms of criticality and relative risk to
the business (so we can start with the assets that matter the most)
·
store the complete failure analysis, whether RCM, MTA or FMEA, along
with all failure modes and the resulting proactive tasks
·
allow you to define all of your health indicators, and the
relationships between indicators
·
enable you to set normal and non-normal values for all health
indicators
·
allow you to set up inspection routes, and acknowledge non-normal
data alarms to drive work into the EAM
With this kind of technology, you can bridge the gap between the
valuable raw asset health data, and the investment you’ve made in
your EAM. This approach gives you a way to drive your maintenance
activities based on actual real time asset health, and to execute
the resulting work efficiently in the EAM. See Figure 3.
Figure 3: Bridge the gap between reliability and the
EAM
The role of the maintenance technician and operators changes to
inspecting specific equipment health indicators, inputting findings
into the reliability software and using reliability software to
alert users to issues. This way “the right work at the right time”
gets to the EAM before equipment failures occur.
Think of a Maintenance Manager viewing actual asset health data with
decision makers in order to justify reliability improvements or
necessary equipment downtime for maintenance repairs. Imagine
maintenance supervisors arriving in the morning and looking at a
computer screen which would show alarms for the assets displaying
health problems instead of walking around the plant looking and
listening for potential equipment failures.
Implement one system at a time - change can happen quickly, and
produce benefits fast
The key to making a solution like this work is to implement one
system/asset at a time. You cannot change the culture of all of the
employees in a plant all at once, but you can change the attitudes
and beliefs of a handful of maintainers and operators fairly quickly
if you show them results. Very few assets are at blame for most of
the plant’s problems so you start with a single asset that
represents high risk to your plant’s business – its and asset that
matters a lot when it fails, and is failing a lot. Involve only the
handful of maintenance and operations employees that know
the system best. Soon, within a couple of months, you will have
turned up the performance of your “bad actor” assets, and you’ll be
amazed at how much momentum you can generate to support pursuing the
next highest risk asset.
Conclusion
In conclusion, connecting reliability to your EAM is key to truly
managing your assets. EAM’s are very helpful in managing the
execution of work, but tools are needed to manage the determination
of the “right work at the right time”. With the right tools, you can
drive maintenance activity from your asset health data. And the
best way to get started is one system at a time, which will result
in significant and rapid financial rewards to your company. Written
by Ricky Smith, CMRP
ricky.smith@ivara.com
|
™
