The 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;
• parameter design; and
• tolerance design.
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
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
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 :
L = k ( x - a )
where L = the loss to society of a unit of output at value x
a = the ideal state target value, where at a, L = 0
k = a constant
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
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.