SIX SIGMA AT A GLANCE

SIX SIGMA AT A GLANCE
26. October 2019
Six Sigma is a management system for process improvement. The core element is the description, measurement, analysis, improvement and monitoring of business processes by statistical means. By using Six Sigma, the number of faulty processes, products or services can be reduced to a minimum, resulting in increased cost efficiency, increased sales and higher customer satisfaction.

Six Sigma improvement projects are led by specially trained employees. Six Sigma’s leadership psychology concept is based on role definitions that are aligned with the rankings of Japanese martial arts.

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Where does the Six Sigma concept come from?

Six Sigma was named after a statistical concept in which a process contains a maximum of 3.4 defects per million opportunities (DPMO). Six Sigma can therefore also be regarded as a goal in which not only are fewer errors made in processes, but this is also constantly achieved (low variance).

Six Sigma was developed by Motorola in 1986 and has since helped companies in every industry save billions of dollars.

Simply put, Six Sigma reduces variance so that products and services can always be delivered with their intended quality and reliability.

 

Six Sigma Statistik

Six Sigma is based on a statistical concept: erroneous processes can be minimized if 6 standard deviations (6 sigmas) between the process average (mean µ at the peak of the normal distribution) and the upper and lower specification limits are maintained.

Values outside the specification limits are highly unlikely even if the normal distribution curve is shifted by 1.5 σ to the left or right. Thus, if a process gradually deteriorates over a long period of time, Six Sigma allows a kind of safety zone.

To increase the process sigma level, you must reduce the variance:

Six Sigma zur Verringerung der Varianz
Six Sigma – Mit statischen Methoden die Varianz von Prozessen verringern

A lower variance in the service provision of your products and services enables you:

  • Better forecasting and predictability in the process
  • Less scrap and rework required, reducing costs
  • More efficient products and services that can be used for longer periods of time
  • Happier customers

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