#29 LEAN in the Lab 6

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.


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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

[email protected])

#29 LEAN in the Lab 6

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