Maintenance Technology August 2017 - 22

RELIABILITY & MAINTENANCE

Too much unnecessary data can obscure crucial
information on asset and process conditions.
they have, the more planned and organized they can be. To
that end, they should set warning alarms that allow time to
plan and action alarms that indicate when prompt intervention is required. These alarms, and the data they generate, are
an important part of the solution to the risk-identification
and -mitigation equation, in that they help determine asset
condition. As Berriman emphasized, however, "The information must still be acted on."

Data and maintenance programs
Regardless of industry sector, type of operation, or location,
one constant is the basic maintenance process. All plants
need to complete the following six steps to be consistent,
strong performers
1. Identify work. Maintenance work is identified through
a variety of sources. Most work should come from PM/PdM
activities and the previously described warnings and action
alerts. However, there will be issues identified by operations
that the program missed, requested improvements, and other
tasks. These issues need to be reviewed and approved before
effort is expended on planning and scheduling.
Work entering the system needs to be reviewed for the
completeness of information and approved before moving to
planning. Known as gate keeping, this requires a dedicated
resource for consistency. Ideally, the gate-keeping role
belongs to Operations, i.e., the equipment owners.
2. Plan work. Planning is where a job is broken down into
a logical sequence of tasks, maintenance craft assigned,
parts ordered, and other resources identified, including such
things as scaffolding and contractors. A good job plan allows
accurate scheduling and work execution. Job plans should
include safety and environmental precautions, work permits,
and other procedures. Data collated at this step should
include equipment data, materials/parts data, work history,
safety/environmental data, and resource availability.
The output of this step is a backlog of planned work to
build schedules and balance workforce composition, especially where contract resources are used to augment in-house
maintenance personnel.
3. Schedule work. This step takes the job plan data for duration and resources, and integrates production-planning data
and asset criticality to create a maintenance schedule that fits
the production schedule. This requires collaboration between
departments to understand priorities, equipment availability,
and other issues. The scheduler role should be owned by
Operations since, again, it owns (controls) the equipment.
The outputs of scheduling are long-range plans and a
weekly calendar of maintenance work used to create daily

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MAINTENANCE TECHNOLOGY

schedules. Daily scheduling is a joint effort to select new
work for the next day from the weekly schedule and to
ensure incomplete work is carried forward.
4. Execute work. When a day's schedule is completed,
Operations can prepare the equipment and Maintenance
can execute the work. This phase includes the integration
of unplanned work that might supersede scheduled tasks,
known as break-in work. This work needs to be managed to
prevent organizations from becoming highly reactive.
Maintenance supervisors need to monitor progress on
work to communicate with Operations and to ensure time is
added to the next day's schedule for incomplete work.
5. Follow up/capture data. Upon completion of work,
data must be captured to drive analysis, planning, and other
activities. That includes capturing "as found/as left" data for
instruments, repair history, failed components, time, materials, and labor, among other things. The information should
then be recorded in the CMMS for future use. Responsibility
for this step typically falls to maintenance technicians and
supervisors.
6. Analyze data. Once data has been captured, analysis can
be performed on failure modes to determine and mitigate
bad actors, or equipment with high costs and downtime.
Cost and lost-production data can be used to understand
budget variances and drive key performance indicators
(KPIs). Reliability teams use maintenance data for detailed
statistical analysis, such as Weibull, that identify patterns of
failure and predict future events.

Navigating your data
According to Keith Berriman, the Industrial Internet of
Things is an opportunity to increase the generation of
accurate timely data without the use of invasive and timebased processes. As the integration of systems improves, the
interconnectedness of data allows more accurate and simplified presentation of information for repair/replace decisions.
"But," he cautioned, "too much unnecessary data can
obscure the information personnel are looking for and hide
problems that might become critical and dangerous. While
technology is a great enabler, without a strong foundation,
it won't deliver the results plants seek. "The key," Berriman
concluded, "is to be able to identify and then act on the right
data." Looking to specific "stars" in your plant is a good way
to ease that voyage. MT
Keith Berriman P.Eng, CMRP, is a senior reliability consultant
for Emerson (emerson.com), based in Edmonton, Alberta. For
more information, email Keith.Berriman@Emerson.com.
AUGUST 2017

http://www.emerson.com

Table of Contents for the Digital Edition of Maintenance Technology August 2017