Design of Experiments
DOE - Design of Experiment
DOE is an approach used to identify factors/steps that are contributing most to an observed variation in product specifications. The classical DOE focuses on identifying the factors that affect the level of a product/process response, examining the response and forming the mathematical prediction model. The modern DOE, introduced by Genichi Taguchi in early 1980s, applies in both product and process development to identify the factors that affect the variability of the response.
One important use of DOE is to find the tolerances and nominal values, called Parameter Design, that will achieve design goals. In Taguchi method, it is to make the performance as insensitive as possible to variations of parameters that cannot be controlled easily. Allowance design is where tolerances are found for each parameter. Tolerances are larger where variation has little affect on performance. On the other, tighter tolerance, which are costly, are specified for parameters having variation that greatly effects performance. The premise behind this method is that the amount of variation in the performance of a design is affected much more by some parameters than by others. Also, the amount of variation in performance may possibly be changed by choosing different nominal values.
Tolerances can be relaxed on those parameters without affecting the performance a great deal. Figure below shows an example of this. However, some parameters must not vary from the nominal value too much. If they do, there will be a large variation in the performance. For this, the design is said to be very sensitive to the parameter. In the figure, such a parameter is labeled as width. On the other hand, some parameters can vary a great deal from nominal and have little effect on performance. For this, the design is said to be not sensitive to the parameter. This is shown by label height in the illustration. Tolerances will be tight for the parameter labelled as width, but can be
DOE is an approach used to identify factors/steps that are contributing most to an observed variation in product specifications. The classical DOE focuses on identifying the factors that affect the level of a product/process response, examining the response and forming the mathematical prediction model. The modern DOE, introduced by Genichi Taguchi in early 1980s, applies in both product and process development to identify the factors that affect the variability of the response.
One important use of DOE is to find the tolerances and nominal values, called Parameter Design, that will achieve design goals. In Taguchi method, it is to make the performance as insensitive as possible to variations of parameters that cannot be controlled easily. Allowance design is where tolerances are found for each parameter. Tolerances are larger where variation has little affect on performance. On the other, tighter tolerance, which are costly, are specified for parameters having variation that greatly effects performance. The premise behind this method is that the amount of variation in the performance of a design is affected much more by some parameters than by others. Also, the amount of variation in performance may possibly be changed by choosing different nominal values.
Tolerances can be relaxed on those parameters without affecting the performance a great deal. Figure below shows an example of this. However, some parameters must not vary from the nominal value too much. If they do, there will be a large variation in the performance. For this, the design is said to be very sensitive to the parameter. In the figure, such a parameter is labeled as width. On the other hand, some parameters can vary a great deal from nominal and have little effect on performance. For this, the design is said to be not sensitive to the parameter. This is shown by label height in the illustration. Tolerances will be tight for the parameter labelled as width, but can be