The ideas behind the Six Sigma concept arose from a realisation that technology changes the way we should think about quality and especially about manufacturing non-conformance rates. When automated processes are responsible for much of current manufacturing, quality levels should be very high. Thus, a change was required in the way organisations think about what is acceptable in terms of non-conformance to agreed quality levels. That change was to move from expressing and measuring quality levels in percentages, or parts per hundred to one of adopting parts per million or even parts per billion.

From this concept and statistical underpinning Six Sigma has developed into a highly disciplined process used to help an organisation focus on developing and delivering near-perfect products and services. The basic approach is to identify and evaluate a defect, analyse the causes, make improvements, and then control those improvements. Many of the tools of Six Sigma (and the concept of lean manufacturing with which Six Sigma is most closely identified) can be found in statistical process control, total quality management, statistics, process improvement, inventory control and operations management textbooks. However, it is not just the tools that deliver Six Sigma performance - it is the logic, discipline and practical application that drives the search for perfection. | ## Sigma (σ)is a letter in the Greek alphabet used to denote the standard deviation of a Normal distribution. The outputs of a process usually form a normal distribution so 'sigma quality levels' can be used to describe the output of a process, expressed as the deviation of the process from its quality norm. A Six Sigma quality level is said to equate to 3.4 defects per million opportunities. This is actually a little strange since if a normal distribution table is consulted (very few go out to ± six standard deviations or six sigma), one finds that expected nonconformances are 0.002 parts per million (two parts per billion). The difference between this figure and the 'official' six sigma figure of 3.4 defects per million parts is because, when the concept was established, it was assumed that a typical process mean could drift 1.5 sigma in either direction. The area of a normal distribution beyond 4.5 sigma from the mean is indeed 3.4 parts per million. Because control charts will easily detect any process shift of this magnitude in a single sample, the 3.4 parts per million represents a very conservative upper bound on the nonconformance rate. |

The aim is to ensure that all outputs meet customer specifications. This is very intuitive for manufacturing and industrial businesses; but as Six sigma is extended to new sectors, this can potentially be a new concept for transactional businesses. Customer needs must be understood down to the 'tolerance' level.

Data is necessary to identify input, process and output areas for improvement. Quality improvements are not haphazardly implemented. Instead, resources are assigned to projects where it can be shown through data analysis that the customer will feel a difference. With Six Sigma, statistics provide objective evidence on which decisions are based. So a common approach is to identify a practical problem, convert it into a statistical problem, derive a statistical solution and then transform that to a practical solution. (This is the basic modelling approach.)

The entire company must back the concept to make it work. Often employees have improvement ideas but not the skills to 'sell' their idea or the resources to translate it into production. Those practising Six Sigma are awarded 'belts' as in martial arts to recognise training and experience and a Six Sigma black belt is highly prized both by its recipient and by the employer of that recipient.

Six Sigma has moved from the 'problem consideration' to the 'design' phase. The aim of many Six Sigma programmes is to design and engineer quality into the process as a proactive approach to defect elimination.

The application of the basic Six Sigma concept now goes beyond its original area of defect reduction to emphasise business process improvement in general. Thus Six Sigma programmes may include cost reduction, cycle-time improvement, increased customer satisfaction and any other metric important to the company. Thus, Six Sigma now implies a whole toolbox and a whole culture of improvement using a variety of tools and statistical methodologies to improve the bottom line of companies.

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Provided by John Heap

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