Creating the CRT
In the last blog we discussed the basic elements of the Current Reality Tree (CRT), with the promise to share a CRT from a real situation.
In the last blog we discussed the basic elements of the Current Reality Tree (CRT), with the promise to share a CRT from a real situation.
Without revealing company names, let’s start
with some background on the particular company. They are a major producer of electronic
components, mostly in the form of circuit cards. They are major supplier to
other companies in the electronics industry. The plant was configured with
seven (7) major assembly lines. Most lines were dedicated to certain types of
boards, but there was also several with cross-functionality. In other words,
the same type of board could be produced on more than one line. The most
notable problem, and the reason they called us, was they were suffering from
very high levels of WIP and not being able to meet on-time delivery demands
from the customer.
We started our analysis with them by
interviewing the workers on the line. We were first looking for the perceived
UDE’s that existed.
Collecting UDE’s
The UDE’s provide a very important piece of
the puzzle you are trying to solve. But, BEWARE: Not ALL UDE’s are really
UDE’s. It’s important when you collect UDE”S to have people write them down in
the form of answering a question. For exmple; “When I think of the current
system, it bothers me that…” The “that statement” becomes the UDE. The more
people you talk with, the better the UDE list will become. Another important
factor is to note the commonality between statements. Five or six different
people might all say something different, but all six mean exactly the same
thing. When you find an UDE that fits this category – you’ve found an important
UDE. It is also important to filter the UDE’s – to separate those emotional
statements from logical statements. As an example, suppose during the UDE
collection someone responds back to the statement with “It bothers me that my
boss is an idiot!” No matter how true that statement may, or may not be, it is
an emotional statement and not a logical statement. Spending the necessary time
on the front end to filter the UDE’s, can translate into a much smoother process
when constructing a CRT.
With that said, here is the final UDE list
developed for this company:
1. The front of the line is measured in
utilization minutes.
2. The back of the line is measured in boards
per day.
3. RM’s are sometimes not available for
production runs.
4. Testing takes too long to complete for some
boards.
5. FTC and CQA perform the same function.
6. Some test equipment is not effectively
used.
7. 100% of the boards are tested.
8. Boards can be rejected for cosmetic reason
and not functionality.
9. Some batch sizes for some boards are too
large.
10. Some FG’s sit in testing waiting for
transfer to FG inventory.
11. Testing is not considered part of the
production line.
From the 30 or so different UDE’s collected
the list was reduced to the above list. Each UDE seems to be a separate problem, with no clear correlation between them, and each is causing its fair share of
Undesirable Effects in the system. So, the hunt was on to discover correlation
between the UDE’s and surface a probable Root Cause.
Constructing the CRT
With the UDE list, we are trying to build
correlation between the entities. In other words, are there any two of these
entities where one can cause the other? When you find those two, it becomes the
starting point to build the rest of the CRT. Continue building until all, or
most of the UDE’s, have been connected. Figure 1 shows how these entities were
connected to show the CRT. You’ll notice that the entity boxes each contain a
number at the top. This is nothing more than an entity address. This method
helps when scrutinizing using the CLR’s to be able to point out entities
quickly in order to make a connection. Those entity numbers with an asterisk
(*) were entities from the original list. You will also notice some entity
numbers without an “*”. These entities surfaced during development of the CRT
as predicted effects and additional causes from the CLR’s
Using the CRT to formulate the sufficiency
based logic you can see that from the original UDE list, we were able to show
cause-effect-cause relationships between all of these undesirable effects. The
root cause in this example WAS NOT an entity listed in the original list, but
rather a root cause that was exposed because of the CRT. In this case it was
policy constraints. I say constraints as plural because this company has so
many measurements they were trying to record, and some of these measurements
were in direct conflict with each other. You’ll notice at the bottom of the CRT
the two measurements – one for minutes and one for boards. In their mind, high
machine utilization was equal to producing lots of boards. They had very
expensive equipment and the only way they could justify the equipment was to
keep it busy all the time. Because of this measure, they continually loaded the
system with work, which created a vast amounts of work-in-process (WIP) inventory, much
longer lead times, and consequently missed due dates.
In the end, policy measurements were changed,
or eliminated, and the system was structured as a Drum-Buffer-Rope system with
the test equipment being the drum. By using the test equipment as the drum we
were able to release (“pull”) work into the system at the correct rate. This
was a much different environment than trying to “push” work into the system for
the sake of efficiency. The overall WIP reduced dramatically, the lead-times
were shortened to hours rather than days, and on time delivery skyrocketed.
Revenue jumped $350M in 6 months time and all because a CRT helped them
understand what the real root cause was.
In the next blog we will
discuss the Conflict Diagram and review some basic principles for its use and
structure.
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