Product and Process Comparisons
|Outline for this section||
In many manufacturing environments it is common to have two or
more processes performing the same task or generating similar
products. The following pages describe tests covering several of
the most common and useful cases for two processes.
||Example of a dual track process||
For example, in an automobile manufacturing plant, there may exist
several assembly lines producing the same part. If one line goes
down for some reason, parts can still be produced and production
will not be stopped. For example, if the parts are piston rings
for a particular model car, the rings produced by either line
should conform to a given set of specifications.
How does one confirm that the two processes are in fact producing rings that are similar? That is, how does one determine if the two processes are similar?
|The goal is to determine if the two processes are similar||
In order to answer this question, data on piston rings are
collected for each process. For example, on a particular day,
data on the diameters of ten piston rings from each process are
measured over a one-hour time frame.
To determine if the two processes are similar, we are interested in answering the following questions:
|Unknown standard deviation||The second question assumes that one does not know the standard deviation of either process and therefore it must be estimated from the data. This is usually the case, and the tests in this section assume that the population standard deviations are unknown.|
|Assumption of a normal distribution||The statistical methodology used (i.e., the specific test to be used) to answer these two questions depends on the underlying distribution of the measurements. The tests in this section assume that the data are normally distributed.|