office, which makes this an appealing one-and-done scenario. Plus, there are mobile
apps for many test tools that make it easy
to transfer data from the situation to the log
and from the individual to the team.
Cloud vs. SCADA
More and more companies are finding it
easy to rely on the cloud: server networks
that can be harnessed for remote storing,
accessing, and sharing of data. The team can
connect any time and from anywhere due
to the mobile processing power resident in
smart phones and tablets. Plus, with more
and more companies using the cloud, it
actually costs less to increase capabilities
in the cloud than it would to increase the
capabilities on in-house systems.
Because cloud computing is often paid
for as a service, it comes from an operations
budget rather than a capital equipment budget. This fact shifts risk over to the service
provider that has to maintain the hardware
and software of the cloud system. Cloud
services also encrypt data and restrict access
far better than most in-house systems that
connect to the Internet.
SCADA systems, on the other hand, are
attractive because they include fixed-mount
sensors that provide automatic data capture
and sophisticated analytics specific to equipment type. They’re the opposite of DIY and
they work 24x7.
That brings us back to ROI. How many
machines in the facility are important
enough and failure prone enough that they
need active monitoring? How complex is it
to gather the data and analyze it? What are
the options to automate the diagnosis, so
that more members of a team can perform
The pinch point comes when a machine,
or some of its key components, starts to
degrade. That’s when any maintenance
team, large or small, wants frequent
measurement data that they can access
remotely. Some teams have begun using
small leave-behind mini-meters that can be
locked into the panel. The meters send data
wirelessly to a master meter or computer,
making it easier and faster to complete data
checks more often. Another partial solution
is for any tech in the area to take a thermal
image of the machine and save it to the
cloud where a more senior technician can
evaluate it for change compared to previous
images. Even vibration data collection has
become more automated, such that hand-
held test tools now assess vibration signals
on the spot.
The Soft-Skill Side of
If we take a comprehensive predictive
maintenance list and narrow it down to the
steps necessary for a non-automated, midsized facility, the key points look something
• Know your most important pieces of
equipment and their telltale measure-ments/inspection points that provide
you with specific health information.
• Whenever someone is working on a
piece of equipment, make it standard
practice to check those telltale data
signs and save the data points to a
shared location, organized by equipment type and marked by the date.
• Whenever troubleshooting, check the
data-share first (which could help narrow down to root cause of a malfunction much faster).
• Success often hinges on an in-house
champion, usually either the team lead
or a senior technician. But unlike at a
large facility where predictive maintenance is its own department, at a
mid-size facility, success also requires
bringing the whole team up to speed.
Here are three tactics to consider.
1) Schedule lunch-and-learn sessions with
incentives for skills training. The goal
is for the whole team to discuss telltale
signs of problems as well as the objec-
tives of the predictive maintenance so
that everyone knows what to look for.
These meetings can also provide basic
how-to sessions on cloud-based spread-
sheets and other mobile measurement
apps, using the team’s own smart devices.
As the project gets rolling, the meetings
become a time and place to review the
data logs and discuss inspection and
repair strategies. This shared commu-
nication provides context for the data,
helping the team understand how record-
ing isolated measurement points makes a
difference when aggregated over time.
2) Assign the task of regularly assessing the
accumulated data. This is when trends
analysis happens. Look for changes that
might indicate a problem; in general, a
measurement that deviates by five or ten
percent of norm may need investigation.
Also, the team should be encouraged to
check the log while they’re on the job,
not just for data entry. In fact, a standard maintenance form can include a
simple check-off indicating the data has
3) Incentivize suggestions and data sharing between team members. Reward
people who speak up when they
notice something that could enter into
a telltale category or who come up
with other ways to use the cloud log
and their data sharing to improve team
Changing the ROI Equation
Not all businesses have the budgets to
implement a dedicated predictive maintenance system, but they do have smart
devices that can be incorporated into daily
use, raising the overall effectiveness of even
a small maintenance team.
Industrial facilities that are trying to ramp
up production may be especially prone to
delaying regular maintenance, increasing the
likelihood of emergency repairs that spread
lean teams even further. To truly optimize
the crew that you have, invest a little time
in a cloud-based data tracker, some wireless tools, and some training to pull it all
together. When the entire team has access
to maintenance data, better decisions can
be made at lower cost, before an emergency
ensues — and that’s an ROI equation most
of us can get behind.