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TAGUCHI METHODSThe term 'Taguchi methods' is normally used to cover two related ideas. The first is that, by the use of statistical methods concerned with the analysis of variance, experiments may be constructed which enable identification of the important design factors responsible for degrading product performance. The second (related) concept is that when judging the effectiveness of designs, the degree of degradation or loss is a function of the deviation of any design parameter from its target value. These ideas arise from development work undertaken by Dr Genichi Taguchi whilst working at the Japanese telecommunications company NTT in the 1950s and 1960s. He attempted to use experimental techniques to achieve both high quality and low-cost design solutions. He suggested that the design process should be seen as three stages:
Systems design identifies the basic elements of the design, which will produce the desired output, such as the best combination of processes and materials. Parameter design determines the most appropriate, optimising set of parameters covering these design elements by identifying the "settings" of each parameter which will minimise variation from the target performance of the product. Tolerance design finally identifies the components of the design which are sensitive in terms of affecting the quality of the product and establishes tolerance limits which will give the required level of variation in the design. Taguchi methodology emphasises the importance of the middle (parameter design) stage in the total design process - a stage which is often neglected in industrial design practice. The methodology involves the identification of those parameters which are under the control of the designer, and then the establishment of a series of experiments to establish that subset of those parameters which has the greatest influence on the performance and variation of the design. The designer thus is able to identify the components of a design which most influence the desired outcome of the design process. The second related aspect of the Taguchi methodology - the "Taguchi loss function" or "quality loss function" maintains that there is an increasing loss (both for producers and for society at large), which is a function of the deviation or variability from the ideal or target value of any design parameter. The greater the deviation from target, the greater is the loss. The concept of loss being dependent on variation is well established in design theory, and at a systems level is related to the benefits and costs associated with dependability. Variability inevitably means waste of some kind - but operations managers also realise that it is impossible to have zero variability. The common response has been to set not only a target level for performance but also a range of tolerance about that target which represents 'acceptable' performance. Thus if performance falls anywhere within the range, it is regarded as acceptable, while if it falls outside that range it is not acceptable. The Taguchi methodology suggests that instead of this implied step function of acceptability, a more realistic function is used based on the square of the deviation from the ideal target, i.e. that customers/users get significantly more dissatisfied as performance varies from ideal. This function, the quality loss function, is given by the expression :
A common criticism of the Taguchi loss function is that while the form of the loss function may be regarded in most cases as being more realistic than a step function, the practicalities of determining the constant k with any degree of accuracy are formidable. Quoted successful applications of the Taguchi methodology are frequently associated with relatively limited aspects of design, for example single parts, rather than very complex products or services. Some designers and academics also argue that the results of Taguchi methodology may not always provide better design solutions than obtained by conventional means. However, the critics often seem to miss the point - that Taguchi methods are not just a statistical application of design of experiments; they methods include the integration of statistical design of experiments into a wider and more powerful engineering process. The true power of the methodology comes from its simplicity of implementation. The methods are often applied on the Japanese manufacturing floor by technicians to improve their product and their processes. The goal is not simply to optimise an arbitrary objective function (which is how Westerners often regard them) but rather to reduce the sensitivity of engineering designs to uncontrollable factors or noise. The objective function used is the signal to noise ratio which is maximized. This moves design targets toward the middle of the design space so that external variation effects behaviour as little as possible. This permits large reductions in both part and assembly tolerances which are major drivers of manufacturing cost. See Taguchi, G., El Sayed, M. & Hsaing, C. (1989). Quality engineering and production systems. New York: McGraw-Hill.
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