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Considerations for Planning and Scheduling
by Howard W Penrose, Ph.D., CMRP, President,
SUCCESS by DESIGN
Introduction
Planning and scheduling tasks tend to be based upon fixed times
in both the internal and contracted maintenance arena. This can
lead to inefficient or ineffective use of resources and the
decline of the maintenance department towards reactive
maintenance, further reducing the efficiency of the program.
There are a number of ways to not only ensure proper completion
of maintenance tasks, both scheduled and reactive, but also to
improve wrench time.
In the production and operations arena, there are a number of
methods of scheduling production for maximum efficiency. The
method for getting the most out of the process is by
determining, first, if the production method is a job shop,
batch, assembly line or continuous flow. Once operations has
determined the type of process, scheduling can be performed
using simple methods, with unknowns including suppliers and
uptime. In fact, some planning methods review production and
take into account reduced throughput due to improper maintenance
without realizing it.
Maintenance is slightly different in that it can be a
combination of all four systems. For instance:
-
Reactive
Maintenance (RM): This is a job-shop process where each
repair and return to service is handled on a case-by-case
basis.
-
Preventive
Maintenance (PM): Depending on the type of PM, this can be
job-shop, batch or assembly.
-
Predictive/Condition-Based Maintenance (PdM/CBM): These are
generally batch or assembly with continuous monitoring
falling under continuous flow.
Add in the variable of individual training, experience and aging
of the workforce, planning and scheduling can become quite
complex, with the added issue of production and operations
departments that may not turn over equipment for maintenance.
As a result, many planning and scheduling philosophies take the
easy way out and over-schedule work. This leads to frustration
on the part of the workforce from never being able to catch up
to their daily workload. The result tends to be falling back on
performing tasks in the exact amount of time outlined by the
task and a growing lethargy, or even unnecessary overtime to
meet PM task completion.
In this paper, we will discuss how to bring these different
issues in line in order to develop a consistent strategy to
improve your wrench time. The improved efficiency and
effectiveness of your maintenance department will provide
additional resources from your existing assets, or will help
identify the lack of assets that is impacting your company.
The Workflow Concept
The Workflow Concept (WFC) is derived in the same way that
workflow is determined for production, including the methods of
Design for Manufacturing and Assembly (DFMA), in which our
concept is Design for Maintainability (DFM). Does this refer to
changing the design of equipment when it is purchased?
Somewhat. However, it also refers to designing the maintenance
process around the actual maintenance requirements. In effect,
a part of DFM includes such processes as Reliability-Centered
Maintenance (RCM) which is a tool used to determine the optimum
maintenance for a system.
The concept of RCM provides the information of what the optimal
maintenance requirements are, with evidence for that
maintenance. The concept of DFM provides the methods for
assisting the RCM process in determining budget requirements
while also providing information on individual manpower
requirements based upon the resources available. It is much
like a sports team in that if you coach to a strategy, then your
season will be poor; if you coach and develop your strategy to
the capabilities of your players, you will do very well. In
this case, we are going to look at the capabilities of our
personnel and resources and match them to the maintenance
development process strategy.
The concepts of WFC and DFM are not unique. They were born of
the efforts of production and operations sciences and industrial
engineering. The primary difference is we are going to match
these traditional manufacturing principles to the application of
maintenance scheduling and planning. This is not a significant
leap nor is it particularly complex.
Components of the WFC:
-
Determining the maintenance task requirements through
processes such as RCM;
-
Performing
time and training studies in order to determine the time
necessary to perform tasks and to determine optimal methods
for performing the tasks;
-
Development of best practices to match the optimal task
methods. These should be created in terms of processes and
may include times for actual steps;
-
Determine
qualifications of individual maintenance personnel for these
practices;
-
Benchmark
existing or similar best practices and determine the gap
between these benchmarks and existing personnel
capabilities;
-
Develop
goals for the individual personnel based upon the gap; and,
-
Schedule
according to the capabilities of personnel.
For the purposes of this paper, we are going to assume that the
RCM process has been completed and we are determining the DFM.
Time Studies
The idea of the time study goes back to the early days of
Scientific Management. The idea is to break up a task into
manageable chunks and determine the times for each step. The
result of a time study can provide the following information:
-
Which
tasks, or combination of tasks, can complete the steps the
fastest while maintaining quality of work and safety;
-
What
resources are required for each portion of the task,
including personnel requirements; and,
-
The total
man-hours and linear man-hours required to perform the tasks
by individual or by projecting based upon experience and
training.
Time studies are often seen in a negative light by personnel,
leaving it up to the individual manager, or team, to determine
the best way to approach this most important step in the
maintenance management process. The tools of the trade, from a
technical standpoint, however, are a timer and a notepad. As we
are assuming that such a study has not previously been
performed, the notepad should be used to take notes on the
individual steps and the times to perform each one.
Observations by the analyst should also be noted including the
quality and safety aspects of the work being performed.
The analyst must have experience in the types of tasks that are
being performed with the optimal person having actually
performed the tasks in the past. All records developed must be
kept for future analysis to assist in review of the maintenance
process through such programs as the Maintenance Effectiveness
Review (MER).
A
proper time study includes the development of a sampling
strategy which includes the number and experience/training of
the personnel and the number of task cycles to be studied. This
can then be used to develop a minimum, maximum and average task
time which is necessary to understand task flow and for
scheduling purposes.
The number of task observations, per task, across the
experience/training of personnel should be broken into
increments and the percentage of each group to the population of
personnel should be determined. The number of task observations
can be determined as shown in Equations 1 and 2, where:
·
E = Absolute Error
·
p = Percentage occurrence of activity or delay
being measured
·
N = The number of random observations (sample
size)
·
Z = The number of standard deviations for the
desired confidence of the study:
o
Z = 1.65 for 90%
o
Z = 1.96 for 95%
o
Z = 2.23 for 99%
Equation 1: Absolute Error

Equation 2: Required Sample

For instance, if you have 120 maintenance personnel and you are
examining a motor greasing program in which an average of 25
motors are greased in an 8 hour period and you know that the
personnel performing the greasing are utilizing approximately 5
hours per day. When reviewed, you have 20 personnel who are
fully trained with experience in greasing, 30 who are trained
but with only a little experience, 35 who are familiar with
motor greasing and 35 who are not. That would be 17%
experienced, 25% with some experience; and 29% of each of the
others, and then the number of samples would be spread across
the appropriate personnel. The Absolute Error would be 9.8%
(0.098), when considering all 25 machines and the required
sample for 95% confidence would be 49 tasks. If reviewing all
120 personnel, the 49 tasks being studied would be extended as
follow:
·
Experienced: 49 * 17% = 8
·
Some Experience: 49 * 25% = 12
·
Familiar: 49 * 29% = 15
·
Unfamiliar: 49 * 29% = 14
The analyst will have to determine which mix of personnel are
selected for each of the time studies. This particular approach
will also provide us with an estimation of the training gap time
from each of the levels to the next, along with training and
experience records for each level.
For the time study, itself, a linear breakdown, number of
personnel and times for each step of the task should be
described and diagramed by the analyst for each of the tasks
being reviewed. The actual times are multiplied by a
performance rating that may be above or below ‘1’ depending upon
the analyst’s observation that the observed personnel are
working faster or slower than normal.
Using the above example, the tasks for the first experienced
maintenance person are determined as follow:
-
The
equipment to be greased is tagged out;
-
Grease
plugs are removed and a brush inserted to loosen and remove
any hardened grease, the grease nipples are cleaned;
-
A measured
amount of grease is inserted into the grease nipple;
-
The tag
out tag is removed and the motor is operated;
-
The motor
is turned off and the grease plugs are re-inserted, then the
motor is released for duty.
The times and personnel involved are diagramed as shown in
Figure 1.
Figure 1: Flow Diagram (PERT Chart)

The total linear time is 3 hours and 10 minutes which deviates
significantly from the projected 1 hour and 45 minutes. When
the notes from the analyst are reviewed, it is determined that
the maintenance person was called away for other tasks and
meetings during and between tasks. In the task blocks in Figure
1, the top row is the projected time for each task and the
second row is the actual time in linear hours. The actual
man-hours for this task can be determined as 2 hours and 3
minutes for one person and 1 hour and 5 minutes for the second
person. In maintenance reviews, this particular experienced
maintenance man was determined to be slow.
A second experienced maintenance person is studied. In this
case, the maintenance man does not tag out the electric motors
or run them after greasing. Instead, his tasks read as follow:
-
The
motor is left energized;
-
Grease
plugs are removed;
-
Grease
is pumped into the bearings until fresh grease shows from
the grease plugs;
-
The
grease plugs are replaced and the motor is returned to
service.
The total time per motor is determined to be 25 minutes and only
one maintenance person required. The times across all
experienced personnel average out to 1 hour and 46 minutes,
close to the original time projected. However, the greasing
practices vary between the two extremes noted above. This is
also observed with all the other levels, whose times run as
shown in Table 1 (Note that normally the average should be
weighted but is not in this example).

Because of the dramatic variation in hours, deviation from 9.8%
error and steps at each level, a review of industry practices is
performed and it is determined that the first example, above
(Figure 1) follows the industry best practice. It was also
noted that the fastest time (25 minutes) also resulted in the
greatest number of bearing failures following greasing PM’s.
However, the total man-hours benchmarked is the original 1:45
minutes. The analyst reviews the notes and observations and
makes the following calculations:
·
Step 1: 0:15 hours * 1 = 0:15 hours
·
Step 2: 0:30 hours * 0.85 = 0:25 hours
·
Step 3: 0:03 hours * 2 = 0:06 hours
·
Step 4: 0:50 hours * 0.85 = 0:42 hours
·
Step 5: 0:25 hours * 0.85 = 0:21 hours
It is also reviewed and determined that the lockout/tagout
procedure only requires one maintenance personnel. The same
review is given to the rest of the experience levels and the
results are shown in Table 2.

As noted, the actual average hours were equal, or close, to the
original average hours. This allows the planner/scheduler to
view each level of experience with set Upper and Lower Control
Limits (UCL/LCL).
Training/On-The-Job Training and the Gap
With the information shown in the example, along with
information on training and experience of the associated
personnel, the gap can be evaluated as well as the time to bring
less experienced personnel up to speed. For the purposes of the
example that we have been using in this article, we will assume
that the average training and experience is as follows:
·
Experienced: 2,000 hours lubrication experience and training.
Some gap required for some of the personnel once the new
greasing best practices have been put in place.
·
Some Experience: 1,000 hours lubrication experience and
training.
·
Familiar: 500 hours lubrication experience and training.
·
Unfamiliar: No experience.
Figure 2: Experience and Average Hours

Through the development of this curve, the learning gap can be
estimated. This is extremely important as it provides evidence
of the required training and OJT experience in order to improve
times. When planning personnel, it also provides the
information necessary to determine the gap between experienced
personnel who may be retiring and new personnel hired. This
learning curve and the time study should be re-performed at a
scheduled point after the best practice has been in place, such
as 6 months to a year, in order to measure the impact of the
best practice procedure and to correct any errors in the time
study.
Identifying Other Losses
There are a number of losses and concepts for improving the
efficiency of tasks, such as the one used as an example in this
paper. As part of the exercise of WFC and DFM, the lost time is
reviewed and maintenance process design methods are
investigated. For this we will introduce a second example
before returning to our first one.
In this example, we will consider a motor repair shop department
which is a job-shop scheduling environment. The initial study
was performed in order to determine why the time per repair was
increasing, wrench time was decreasing, on-time deliveries were
non-existent and the warranty rate was also increasing. A new
supervisor was introduced into the department who had WFC/DFM
experience. During 30 days of observation, it was noticed that
customer service personnel would bypass the supervisor and
approach repair technicians directly throughout all departments,
usually their favorite technician regardless of capability and
training. The usual instructions were to stop work on one job
and start another ‘emergency’ job at which point work would stop
on the task that the technician was working on in order to start
another job. In some cases, a few technicians would work on
more than one job simultaneously because upper management would
approach them directly on their increased times to complete
work. The observation was that on 75% of jobs that were
interrupted, additional work was missed on disassembly task
reports, resulting in improper quotations, and steps were missed
in the reassembly of motors resulting in warranty repairs. On
jobs that were not interrupted, these issues occurred in less
than 1% of the work. The average billable time per technician,
in an 8-hour shift, was 4.5 hours, resulting in huge
profitability losses and increased operating costs. During this
time, the supervisor also evaluated the capabilities of the
technicians and performed time studies based upon the time cards
turned in for each job. There were 12 customer service reps and
45 shop personnel with 12 being in the supervisor’s department.
The new supervisor implemented several best practices that had
been observed in other repair shops. All repair requests had to
be passed through the supervisor who would then schedule the
appropriate personnel to perform the work. Emergency jobs would
be scheduled as the next-in-line and/or spread between routine
jobs, with past-due jobs receiving priority. No tasks would be
interrupted for any reason and a second person had to sign off,
as well as the technician, any quality control checks.
In this case, the primary gap had more to do with a culture
change. It was also noted that the size of the jobs in the
small/medium motor department caused the problems to be more
noticeable because of the times and volume of work involved.
The supervisor estimated three months to have all the kinks out
of the new program during which time he had to deal with
customer service personnel complaining to upper management in an
attempt to return the environment to where it was. The primary
complaint being that they did not feel they were able to meet
customer expectations due to scheduling issues.
At the end of the three month gap, the study was performed a
second time over a one week period and warranty, time and
wrench-time being re-measured. Another study was performed
quarterly for the remainder of one year from the implementation
of the plan. The first thing that was noticed is that the
warranty rate dropped to zero almost immediately on jobs
performed following the program implementation. The second
thing noticed was that the average wrench time increased to 7.5
hours and average task times dropped by over 1/3rd
during the first quarter and leveled off at 50% by the end of
the year. In effect, throughput increased almost 400% within
the first year, and warranty rates were virtually non-existent
versus part of the workflow. The concepts gradually flowed
throughout the rest of the repair shop departments during the
first year and profitability increased dramatically while jobs
were being completed on time, and frequently early. As a
result, the next step in the process was to make improvements to
the scheduling and communication systems between the shop and
customer service and sales to improve quoting and delivery
times.
Returning to our original example, there are a number of areas
for improvement to the workflow to increase wrench time and
increase throughput on this particular PM. When reviewing the
linear time to correctly perform the best practice, it was
determined that burdens were placed upon the individual
technicians. While a daily meeting of about ½ hour was
performed to communicate work, gathering equipment, travel and
interruptions took up the remainder of the estimated 2.5 hours.
In fact, it could be considered that the estimated 5 hours
wrench time was overestimated.
The analyst reviews the workflow and notes taken during the 49
observations performed. In this, it is determined that
maintenance personnel are contacted directly by customers and
managers pull the technicians off of jobs, and they are
sometimes made to wait, or are turned away, for production
reasons. At the present time, individual machines are greased
from start to finish before moving on to the next one, in a
job-shop type process. The analyst reviews the list of work and
determines the following DFM strategy:
-
Convert from a job-shop process and perform greasing from a
batch process. This means that instead of tagging out and
greasing one motor at a time, a group of motors is tagged
out logistically close to each other, and the greasing
procedure applied simultaneously on each batch. The number
of motors for each batch is determined by location and
availability to perform the tasks. Each group is broken out
into individual work orders and the time to perform each
group is monitored and scheduled for time study.
-
All
communications with the maintenance personnel must be
directed through the planner/scheduler. The
planner/scheduler has access to the capabilities of each
maintenance technician and their experience related to the
training gap chart.
It is determined that there are ten machines in an average
group. Time studies show that the average time to grease a
batch of ten motors is four linear/man-hours for the experienced
technicians. This reduces the number of technicians greasing
motors from 3 motors per experienced technician per day, or an
average of 6 experienced persons greasing motor per day, to an
average of 2 experienced technicians per day (with variations
due to batch sizes). Task completion improves dramatically and
additional personnel are available for other tasks. With the
reduction of interruptions, the average wrench time improves to
6.5 hours, or 30%, resulting in a wrench time of 81.3% up from
62.5% related to this task. The remaining time is dedicated to
the daily meetings, travel and materials.
Conclusion
The philosophy of WFC/DFM will have dramatic immediate impact
when the ‘hanging fruit’ maintenance opportunities are
identified and improved first. However, most applications will
have very dramatic results. It is also important to gage the
required culture change as all new implementations will meet
with resistance, especially in consideration of time studies and
flow changes.
In the examples used in this paper, we covered job shop and
batch approaches and standard PM’s. However, the concepts
related to WFC/DFM can be applied to all types of maintenance
including emergency maintenance, or reactive maintenance. The
average payback for a WFC/DFM study is measured in terms of days
or weeks. The application of these concepts also bring
maintenance that one step closer to the concepts utilized within
the operations and production departments making communication
between the two groups much improved. Planners/Schedulers can
also use the result of the process in order to more accurately
schedule work so that sloppy practices such as over-planning do
not occur.
In a future paper, we will discuss the application of WFC/DFM to
the reactive maintenance and PdM/CBM processes followed by a
paper on using the method to develop your maintenance budget and
improve planning/scheduling in combination with the RCM process.
About the Author
Howard W Penrose, Ph.D., CMRP, is the President of SUCCESS by
DESIGN Reliability Services. SUCCESS by DESIGN specializes in
corporate maintenance program development, motor management
programs and maintenance and motor diagnostics training. For
more information, or questions, see
http://www.motordoc.net, contact
info@motordoc.net or call 800 392-9025 (USA) or 860 577-8537
(World-Wide).
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