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Six Sigma: Quality management based on statistics

The lean philosophy isn’t the only option when seeking to optimise processes. Six Sigma – a process management method – is no less impressive when it comes to effectiveness.

Having already looked at several lean methods in detail, we are now turning to a similar method for optimising in-house production. However, instead of focussing on throughput time, this method aims to improve quality. Six Sigma is an extremely successful means of analysing and enhancing process quality. Based on a statistical methodology, it can help companies save more than 100,000 euros.

What Six Sigma means

“Sigma” (σ) is the 18th letter of the Greek alphabet. In 1860, Francis Garlton (1822-1911) introduced it as a symbol in the mathematical discipline of statistics. It stands for a variable’s dispersion around its average, or standard deviation. That, in turn, can be traced back to the famous German mathematician Carl Friedrich Gauss (1777-1855).

A six sigma process is one where 99.9996 percent of the elements are error free. In other words, if there are a million opportunities for an error to occur, there will only be – in statistical terms – 3.4 errors.  This number is so low that you could also talk about zero-error production or zero-fault quality. In most companies that have not pursued the corresponding optimisation model, a quality of 3 to 4 sigma is normal, i.e. a success rating of between 93.3 and 99.4 percent. To clarify, if a company has achieved 3 sigma, one million error opportunities will result in 66,807 errors. That leaves a lot of room for improvement.

American-Japanese rivalry

While its predecessor was rolled out in the Japanese shipbuilding industry of the 1970s, the Six Sigma concept was first introduced as such in the USA in 1987. It all started with Motorola. The group was always playing catch-up with its competitors in Japan and it was essential that it found a way to significantly improve product and process quality.

Motorola was inspired by a television division that it used to own and which was now being run by a Japanese company called Mitsushita. The division was more successful than ever before and its televisions were exhibiting 95 percent fewer faults than they did when Motorola was in charge. The new management team had achieved these results by making significant structural changes and applying statistical methods.

Six Sigma finally became popular thanks to General Electric, whose CEO at the time, Jack Welch, declared it the number 1 quality maxim. According to official figures, the method produced two billion US dollars in savings within three years. The Six Sigma concept spread around the world.

Six Sigma: Allocation of roles and hierarchy

Only specially trained employees are deployed in Six Sigma projects. Their roles are described based on the ranking system used in Japanese martial arts such as Karate (i.e. belts) and the hierarchy is governed on a similarly strict basis. We are only going to look at three positions here:

The highest rank is that of Master Black Belt, an individual who has sufficient experience and expertise to train other employees. Green Belts will usually be from middle management level, report directly to the Black Belt and run their own projects and teams. In Japan, companies began to combine Six Sigma with the lean philosophy to get the best of both process optimisation approaches. Combined approaches such as these are given names such as Lean Sigma and Lean Six Sigma.

The DMAIC cycle

The DMAIC cycle is the basis for every Six Sigma project and comprises the following steps – define, measure, analyse, improve and control. It makes existing processes measurable so that they can be continuously improved in order to satisfy customers. These processes are divided into the smallest worksteps possible, which results in numerous individual elements for boosting value creation. These elements are adjusted in relation to both upstream and downstream processes.

The define phase involves identifying and documenting the processes that are to be optimised, the associated difficulties and how the process is to be optimised as part of the Six Sigma project. Next is the measure phase, which is when numbers, facts and figures are recorded for the process under scrutiny. This data is then analysed and evaluated during the analysis phase. The results of that phase are used in the subsequent improve phase to develop measures for effectively rectifying the error causes that have been identified.

During the following control phase, the company monitors the entire process based on statistical means. There are two different intentions behind this – firstly, documenting the functionality and sustainability of the process and, secondly, finding new bases for future Six Sigma projects. The latter point slots neatly into the continuous improvement process (CIP).