This is just an Excerpt from a larger document, click here to view the entire document.Statistical Design of Experiments
Design of Experiments (DOE) is a systematic approach to determining the optimum settings of process parameters. Parameters deemed to be important (usually by an ad hoc team of experts) are varied and the results observed. The simplest form is an experiment in which a high and low value is picked for each parameter and every possible combination is used. For example, a team trying to improve a wave-solder process might suggest varying the temperature, length of exposure and lead/tin ratio of the solder to determine ways to reduce solder defects. A high and low value is selected for each parameter. Every possible combination of high and low values is tested and its effect on solder defects measured. Adding for illustration a test at nominal conditions (i.e. those used before the experiment) the results of such an experiment might be as shown in Table 1.
Table 1
Test
Temp
Length
L/T Ratio
Defect Rate
1
N
N
N
1.5
2
L
L
L
3.2
3
H
L
L
3.1
4
L
H
L
1.9
5
H
H
L
2.4
6
L
L
H
1.6
7
H
L
H
1.6
8
L
H
H
3.3
9
H
H
H
2.2
Table 1 shows that the nominal settings also seem to be the optimal settings. However, we have not discussed other factors that may affect solder defects. These may befactors not under the control of the process owner, and before he accepts the nominal conditions as best, he should examine the robustness of all the settings under varying outside factors. For example, he may get boards of different sizes to solder. Do his test results on one board size hold for other sizes? Does the number of layers in the board make a difference? In our next topic, we shall discuss some methods championed by Genichi Taguchi, which answer such questions. It should be noted that there are various other means for considering robustness, such as randomizing the order of the experiment and repeating it several times, to average out the impact of unknown factors not tested.
It should also be noted that off-on factors, like the presence or absence of a flux in the solder, can be handled by calling the presence of the flux a high setting and the absence, a low setting (or vice-versa). Also, there are tests using more than two settings for some or all factors and fractional factorial test plans that provide more economical testing at the cost of not observing all possible interactions of the factors.
A beginning text on DOE is Understanding Industrial Designed Experiments, by Schmidt and Launsby, published in 1989 by the Air University Press, Colorado Springs.
