In
manufacturing plants like the one I have been consulting for recently, that has limited
human resources, having a well-planned and synchronized production schedule is
critical for the smooth flow of parts through the processes within the manufacturing plant. But as important as the production schedule
is, there are other key factors that must be considered before a viable
production schedule can to be developed.
Perhaps the most significant factor that must be considered is the
degree of operational stability of the equipment being used to produce the
products. That is, if the equipment is
unreliable and unpredictable with excessive amounts of downtime, then it is virtually
impossible to develop a practical and dependable schedule for producing parts. Without stability, the level of
predictability will be very low.
Another
important factor that enters into the production flow equation is the degree of
flexibility of the work force,
especially when a limited number of human resources are employed. That is, if the work force in place is
limited on the number of different machines and parts they are able to run, then
scheduling becomes much more difficult. One could even say that in
circumstances like this, the human resource level might be considered the
system constraint.
Finally,
two other factors that enter into the creation of the scheduling process are
the quality level of parts (i.e. yield) and the demand requirements placed on
each machine/operator combination. If
the yield losses are excessive, then these must be added into the scheduling
assumptions and planned accordingly. For example, if the scrap rate is 5 % on average, then 5 % more parts must be produced to meet demand requirements.
While
all of these factors are important to the development of a viable production
schedule, there must also be an active
improvement plan in place to eliminate the barriers to scheduling. An analysis and review of existing machine
downtime and quality information must be at the forefront of this improvement
plan. A system for capturing this key
data must exist, but unless it is used to its fullest extent to determine the
focal points for improvement, it is just a database.
So
the question becomes one of what should the data analysis look like or what
information is important? Clearly the
reasons for equipment downtime should be available for review, but in what form
should it be displayed? And what about
the quality losses….shouldn’t that be available for review as well? Should the review be only daily information
or should trend analysis also be available?
Obviously daily results are important so that a real time investigation
of the issues can be completed. Memories
fade, so as soon as the data is available, it must be investigated. How an operation is performing, as a function
of time, is equally important because single event problems are not nearly as
damaging as chronic ones. Because of
this, historical plots (e.g. run charts) are very important as well.
My
recommendations for how the data should be analyzed are very straightforward
and simple to understand. Daily results for both
production and quality should be discussed at daily production meetings and
then once per week a simple Pareto Analysis of both downtime and Quality can be
very helpful. In addition, time based
production run charts should be developed to monitor production results as well
as control charts on critical quality measurements. Those responsible for each machine group
should be required to develop and discuss action plans on how they plan to
improve both production and quality.
Once
we have created a more stable production environment, then we can focus on developing a
discrete scheduling system. Drum Buffer Rope (DBR) is a methodology that can
provide relief in a resource starved environment. There
are several key principles behind Drum-Buffer-Rope scheduling that must be understood including:
1. In any set of resources, some will
be more heavily loaded than others which are referred to as Capacity Constraints, or CCR (capacity constrained resource). In some plants there is really only one CCR
while in others, there might be several. The easiest way to locate the constraint is to walk the process and finding the largest pile of WIP.
2. The most capacity constrained
resource will always dictate the rate of work flow from raw materials through to
finished goods. This is an important
concept because knowing where it is will permit us to focus on individual processes and identify each of
their specific constraints.
3. There is no value in having any resource
that feeds the constraint produce at a faster rate than the constraint. Common measurements like manpower efficiency
or equipment utilization might encourage this, but the only outcomes we observe
from using these metrics are increased WIP, extended lead times, more expediting, and deteriorating on-time delivery performance. Plus, the excessive WIP ties
up floor space and cash as well as increasing the chances of part's damage and
undetected quality issues. Both of these
problems can be hidden by the seemingly endless waves of WIP.
4. The production rate of resources
that are fed by the constraint is dictated by the output rate of the
constraint. In other words, the output
of the entire process is dictated by the constraint. Because of this, it is absolutely necessary
to keep the constraints producing at all times.
These
four points lay the foundation for a scheduling system named Drum-Buffer-Rope, so let’s now look at each
individual component of DBR.
The
DRUM
Once the constraint has been
identified, a finite schedule based upon the capacity of the constraint (i.e.
the Drum) must be developed for the work that has to pass through it. The schedule
can be something as simple as deciding the number of parts to produce and must also
include the timing of when each of the parts are due to be completed and
shipped to the customer. In addition, the schedule must also consider normal
yield losses. Essentially the constraint
(the drum) sets the production pace for the entire process.
The
Buffer
DBR’s
buffers exist in two distinctly different dimensions, time and stock. And because the constraint controls the
throughput of the entire process, every minute wasted is a waste of the whole
plant’s production capability. So in
order to get the most out of the plant, employees must get the most out of the
constraint(s). For this reason, we can
never let the constraint be starved of parts.
One logical answer to this is to make sure that there’s always a buffer
of work in front of the constraint so that it is NEVER starved of work. And
although it is a stock buffer, it is created as a result of managing time and
not stock. In other words, parts must be
scheduled to reach the constraint prior to it running out of parts. Let’s look at a simple example.
Suppose
that when raw materials are released into the gating operations of the process,
it takes an average of 27 hours to flow through the different process steps
until they reach the constraint. But because of normal disruptions and
statistical fluctuations, many times semi-finished products would not get there
in time. Things like unplanned downtime,
quality issues or even operator absences happen routinely. In order to counter these delays, we might
want to release the parts and materials hours ahead of when they due at the
constraint to protect the constraint from starvation. In other words, we want to establish a buffer
in front of the constraint. The question
becomes, how long in advance should they be released? One way to calculate this buffer is to determine
the “normal” average length of time from release of materials until they reach
the constraint and calculate one third of this time. In our example, the size of our buffer would
be 27 hours divided by 3, or 9 hours. This
means that if everything flows smoothly, then the work will arrive at the
constraint 9 hours earlier than needed thereby creating a 9-hour stock buffer. The advantage of using this buffer is what
happens when there are disruptions and statistical fluctuation in the processes
in front of the constraint. As long as the
delays don’t exceed 9 hours, then the work will still arrive early or on time
at the constraint.
One
of the most effective ways to monitor the flow of parts so that they will reach
the constraint on time is to create a visual buffer management system. In our example we said that it takes 27 hours
on average from release of raw materials into the process until the
semi-finished parts arrive at the constraints.
We calculated a buffer size of 9 hours to assure that the parts would
arrive on time at the constraint. The
visual buffer management system divides these 9 hours into 3 segments of 3
hours each and color codes them as green (1-3 hours), yellow (4-6 hours) and
red (7-9 hours). If the parts are in the
green zone (i.e. the first 3 hours), then they will most likely arrive at the
constraint on time. If the parts are
late arriving at the constraint and fall into the yellow zone (4-6 hour point),
then plans should be put in place to expedite the parts in the event that they
exceed the 6 hour point. If they pass
into the red zone (7-9 hours), then the plans to expedite should be implemented. This system works quite well as long as the
part’s status is closely monitored.
The
Rope
The
concept of the rope is probably the simplest DBR concept to understand in that the
only parts and materials that should be released into the gating process should
be those needed to support the Drum schedule. And while this may seem obvious, in reality
for many people it isn’t. In many manufacturing
plants work is released into the gating operations simply to keep operators
busy so that workers and machines aren’t idle.
The performance metrics manpower efficiency or equipment utilization are
many times behind this behavior. Many
times batch sizes are inflated to avoid lengthy changeovers so materials are “pushed”
into the process.
So
to summarize:
1. Identify the constraints in the system (this corresponds to the first of Goldratt’s 5 Focusing Steps, “Identify the constraint.”)
2. Examine the orders within the system, consider the finite capacity of the constraint, and schedule the work in detail through the constraint. That is, schedule backwards from the customer due date through the entire process. This corresponds to the second of the 5 Theory of Constraints Focusing Steps, “Decide how to exploit the constraint.”
3. Calculate a time buffer and add it to the average set-up and run times of the processes supplying the constraint. This is also part of TOC’s Step 2 (Decide how to exploit the constraint).
4. Using the rope, only release materials and parts into the gating processes of the plant based upon the needs of the Drum (constraint) and the timing of the Buffer.
5. Monitor the buffer penetration by dividing the total buffer into 3 equal quantities and visually record each 1/3 as green (1/3 of total buffer time), yellow (2/3 of total buffer time) and red (Total buffer time). Green indicates no action is required, yellow requires the development of a plan to expedite the parts, and red requires execution of the expedition plan.
There
are many variations and refinements on this basic technique, but as described
above, it’s one of the keys to dramatically improving the flow of parts through
processes as well as improving on-time delivery performance while at the same
time shrinking lead times and work in progress inventories.
Bob
Sproull
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