7.
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. | ||
