# Six Sigma (6σ)

Six Sigma, represented as ‘6σ’, is yet another important concept that emanate from the Quality Management knowledge area just like Kaizen, PDCA and Just-in-Time.

Six Sigma is a set of tools and techniques for process improvement. Introduced by engineer Bill Smith at Motorola in 1980, it was made central to General Electric business strategy by Jack Welch in 1995.

Six Sigma strategies seek to improve the quality of the output of any process by,

• identifying and removing the causes of defects
• minimizing variability in manufacturing and business processes

## Six Sigma in Action

Several quality management methods, statistical methods are used in the process. A special set of people are developed within the organization that are experts in these methods. Each Six Sigma project carried out within an organization follows a defined sequence of steps and has specific value targets, for example: reduce process cycle time, reduce pollution, reduce costs, increase customer satisfaction and increase profits

## Six Sigma Value

The term Six Sigma originates from terminology associated with statistical modeling of manufacturing processes. The maturity of a manufacturing process can be described by a sigma rating indicating its yield or the percentage of defect-free products it creates.

1 Sigma = 691,462 DPMO = 31% yield and 69% defect
2 Sigma = 308,538 DPMO = 69% yield and 31% defect
3 Sigma = 66,807 DPMO = 93.3% yield and 6.7% defect
4 Sigma = 6,210 DPMO = 99.38% yield and 0.62% defect
5 Sigma = 233 DPMO = 99.977% yield and 0.089% defect
6 Sigma = 3.4 DPMO = 99.99966% yield and 0.00034% defect
DPMO = Defects Per Million Opportunities

Motorola set a goal of “six sigma” for all of its manufacturing.

## Six Sigma and Standard Deviation

To understand the relationship between Six Sigma and Standard Deviation, we can begin with plotting a large volume of data that takes the form of a bell curve. Such distribution is also known as ‘Normal Distribution’ or the ‘Bell Curve’

Standard Deviation is used to measure how far the data is from the mean. In any such distribution, if you go one sigma above and below the mean it covers 68% data. At Six Sigma, the distribution covers 99.99966% of the data

## DMAIC

DMAIC (an acronym for Define, Measure, Analyze, Improve and Control) refers to a data-driven improvement cycle used for improving, optimizing and stabilizing business processes and designs. The DMAIC improvement cycle is the core tool used to drive Six Sigma projects. Note that DMAIC is not exclusive to Six Sigma and can be used as the framework for other improvement applications.

Define – Define the business problem, the customer and the requirements
Measure – Establish performance baselines i.e. how is the process defined, how are the defects measured
Analyse – Identify, validate and select root cause for elimination
Improve – Identify, test and implement a solution to the problem, in part or in whole
Control – Embed the changes and ensure sustainability

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