|
Mistake-proofing
is about getting to the root cause of a problem and then
preventing that root cause from occurring in the future so,
consequently mistake-proofing training must include root
cause analysis training. Here are the root cause
analysis tools we feel are critical to good
mistake-proofing.
The
5-Whys: Ask “why?” 5 (or more) times to tunnel down into the
root cause. The answer to the first why is almost always an
obvious symptom. The secret behind the 5-whys technique is
to accept the answer, but to then ask why again and again
until the root cause is uncovered. Sometimes, the root cause
can be found at the fourth or five why. Often, however, you
must ask “why?” more than 5-times.
What is—What
isn’t Analysis: Often, listing what a problem is and isn’t
helps get to the root cause by a matter of elimination. What
Is-What’s Isn’t questions include: What happened? & What
might you have expected to happen but didn’t? Where did it
happen? & Where didn’t it happen? What changed in the
process? & What didn’t change in the process? Which supplier
was involved? & Which wasn’t?
Data
Collection & Data Display: Fact-based problem-solving –
that’s what root cause analysis is all about. To get facts,
collect data from the process or create data related to the
process. To get facts, we collect data from the process or
create data related to the process. Once data have been
collected, there are a number of simple methods to analyze
data using graphical display techniques. Data display tools
turn the data into pictures and a picture of what has
happened often leads to the root cause.
Failure
Analysis: Techniques for collecting data from failure
analysis include reviewing physical evidence (much like
crime scene investigation), special testing, accelerated testing, and
finite element analysis. You might need special tools or
techniques to review the physical evidence (e.g. microscopy
to look at a break surface) or you might need to conduct
special testing on the product or process itself.
Use
well-designed and easy to use data collection forms. Good
detective skills can turn interviews into effective data
collection events. One of the most powerful, but also most
under-used, data collection tools is a concentration
diagram.
Simulations:
Simulations can be used to collect data using computer
modeling software, pilot-plant experimentation, and if need
be, experimentation using the actual process itself. With
the proper model, a computer could help point the way to the
root cause. Or it might be pilot-plant trials or
experimentation using the “real” process that generates the
data that leads to the root cause. In any case, if you can
recreate the problem, you are more apt to find the root
cause.
Statistical
Analysis: While data display methods are usually easier to
use, sometimes a statistical analysis technique is needed to
wring the real meaning out of the data. SPC control charts
will actively signal a problem with a process. Correlation
and regression analysis and multivariate analysis may be
needed to make sense of the data.
The “Root
Cause” Question: Once you think you are at the root cause,
take a step back and ask yourself the root cause question–
“Does this cause explain all that is known about what the
problem is, as well as all that is known about what the
problem isn’t?“ This
is really a two-part question: make
sure the root cause found fits both the “is” and the
“isn’t” sections of the question. If the cause being tested doesn’t fit both, then it’s probably not the root
cause.
Robin McDermott is director of
training for Resource Engineering, Inc. You can
contact her at 800-810-8326 or 802-496-5888 or by
e-mail. |