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Six Sigma
The ideas behind the Six Sigma concept arose from a realization 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 organizations 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 (parts per hundred) to one of adopting parts per million or even parts per billion. Sigma is a letter in the Greek alphabet used to denote the standard deviation of a process and thus 'sigma quality levels' can be used to describe the output of a process (in terms of 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 sigma), one finds that expected nonconformance's 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. 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. Six Sigma has a customer focus Six Sigma is data driven Six Sigma is inclusive and participative Six Sigma is proactive Six Sigma is spreading.
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