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8/9/2019 #29 LEAN in the Lab 6
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SIX SIGMA
David Plaut
Six sigma (6- sigma), as is true for any process improvement system, seeks to
improve the quality of outputs by identifying and removing the causes of defects
(errors) and minimizing variability in the processes.
In a nutshell, six sigma (6-sigma) can be discussed at three levels: as a
management system, as a methodology, and as a metric (a statistic).
As management system, consider 6-sigma as another in a long series of
approaches to improving almost any process. Similar to 6-sigma are zero defects,
continuous quality improvement (CQI), total quality improvement (TQI) and to an
extent, LEAN. These names all suggest a common goal: improvement in a process
or processes. Each 6- Sigma project is supported by a team with defined
responsibilities and follows a defined sequence of steps and has quantified
targets.
As a methodology we can consider the following as vital ingredients in achieving
the statistical goal of 6-sigma:
y Understanding and managing customer requirements
y Aligning key business processes to achieve those requirements
y Utilizing rigorous data analysis to minimize variation in those
processes
y Driving rapid and sustainable improvement to business processes
The third level, 6-sigma as a metric, is the source of the name 6- sigma. 6-
sigma refers to 3.4 defects per one million opportunities (DPMO). 6- sigma started
as a defect reduction effort (as in zero defects) in manufacturing and was thenapplied to other processes for the same purpose quality improvement. A 6- sigma
project will use management, methods and metrics at the same time.
The metric as something with which you are all familiar for 6- sigma refers to the
Gaussian (bell, normal) curve.
8/9/2019 #29 LEAN in the Lab 6
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As you see in the figure, very little of the area under the curve is to the right or left
of 3 sigmas (the values in the table below the curve are the areas (in per centage)
between the + and number. For example about 68% of the area is between -1
and + 1 SD (sigmas). Virtually none of the curve lies beyond even 4 sigma.
Over time there has been, necessarily, less emphasis on achieving the literal
definition of 6- sigma with only 3.4 defects per million opportunities (DPMO).
Today the emphasis is more on the idea of process improvement or continuingprocess improvement beginning with an understanding of the requirements of
the end user. Some examples of 6-sigma projects are: turnaround time for
cardiac marker results for the ED, the number of contaminated blood cultures,
and improper patient identification.
Once the requirement is defined to the satisfaction of the 6-sigma team (e.g.
doctors, laboratory staff, nursing staff, and phlebotomists), an agreement on
what data need be collected and analyzed is established. Then a protocol isdeveloped to measure the number of defects. In the case of the turnaround
time in the ED, the requirement might be a time from sample collection to a
report to the ED of less than 60 minutes. Thus any sample that took more than 60
minutes to report is a defect. If this happens once for every 100 samples the
defect rate is 1% or 2.4 sigma. In order to achieve a 4 sigma success rate only 1 in
1 2 3 4 5 6
68.3% 95.4 99.73 99.99 99.9999 99.9999998
Lower s ecification level U er s ecification level
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In addition, the 6- sigma model assumes that the process data always
conform to the normal distribution. The calculation of defect rates for
situations where the normal distribution model does not apply is not
properly addressed in the current 6- sigma literature.
Because 6-sigma centers on change, fear of change is an important topic to
discuss in the meetings on how to perform the study and how to implement it. It
as been my experience in talking about changing QC rules that fear of change or
related to it (if not just another way of showing fear of change) is the remark We
have always done it this way. It must work. Something may appear to work
(We dont fail proficiency surveys.) but not in every sense. There may be other
criteria against which work might be defined. In the case of QC the number of
false rejects approaches 10%. These are things that need to be carefullyconsidered as 6-sigma (or whatever name you want to use for process
improvement) is brought up.
There are few if any processes that cannot be improved. 6-sigma is one approach
which has been shown to work, but which is not without its critics. Perhaps an
eclectic approach to process improvement might be a way to incorporate parts of
many of these ideas based on your needs and resources.
(Authors note: I have prepared a bibliography with references to 6-sigma as well as other systems for
improving processes. I will send a copy to you by e mail if you send me a note at