factors to be varied
in the experiment, the ranges over which these factors will be varied, and the specific levels at
which runs will be made. Process knowledge is required to do this. This process knowledge is
usually a combination of practical experience and theoretical understanding. It is important to
investigate all factors that may be of importance and to avoid being overly influenced by past
experience, particularly when we are in the early stages of experimentation or when the
process is not very mature. When the objective is factor screening or process characterization,
it is usually best to keep the number of factor levels low. (Most often two levels are used.) As
noted in Figure l3.-4, steps 2 and 3 are often carried out simultaneously, or step 3 may be done
first in some applications.
3. Selection of the response variable. in selecting the response variable, the
experimenter should be certain that the variable really provides useful information about
the process under study. Most often the average or standard deviation (or both) of the measured characteristic will be the response variable. Multiple responses are not unusual.
Gauge capability is also an important factor. If gauge capability is poor, then only relatively large factor effects will be detected by the experiment, or additional replication
will be required.
4. Choice of experimental design. If the first three steps are done correctly, this step
is relatively easy. Choice of design involves consideration of sample size (number of replicates), selection of a suitable run order for the experimental trials, and whether or not blocking or other randomization restrictions are involved. This chapter and Chapter l4 illustrate
some of the more important types of experimental designs.