This demonstration is going to introduce two examples of how scripts can be used. In one, we'll make new columns and perform analyses with them. And in the other, we'll use a dialog box to generate a custom report. In the course journal in Section I'm going to click Reaction-Injection Molding Temperature Data. I'll go ahead and make the timestamp column wider so we can read the whole value there. And this data table represents a manufacturing process where we have two temperatures of interest. We're going to focus on ISO Temp in this example. And we're going to run a script that will smooth the data, find the minimum and maximum temperatures indicating when a heating cycle ends or begins, and plot both of the minimum and maximum temperatures in separate control charts. Now, we have a script in the data table called Run Chart, and I'm going to click that green play button. Just to illustrate that there is noise in these data, and so we've got-- this is for both of the temperatures again. We'll focus on the ISO Temp. So that's why our script is going to begin by smoothing the data before we try to find where we have these minimum and maximum temperature values. So I'll return to the journal, and I'm going to click the script called Check ISO Temperature Control. And the script will run automatically as soon as I click it in the journal. So we'll go back and take a look at what it did. I'll come up to my menu and go to Window and find the Molding Temperatures Data Table to see how that's been modified by my script. So you can see the additional columns are the moving average of the ISO Temp. And this was calculated using a moving average of points. So I'm smoothing the data in this column. Then, I simply take the difference in the moving average temperatures from one row to the next, and the script identifies where we see a sign change between two rows and then also adds a column called Heating Cycle. And where we see changing from a negative value to a positive, that indicates a minimum where we would turn the heater on. And where we change from a positive value to a negative on those temperature differences, that would indicate a maximum, and we would turn the heater off. Those rows are then selected, and if I navigate to the other open data table right now, you can see that those rows have been pulled out into a subset data table. And the script ran an analysis using the control chart builder, which is here in the background. These separate individual measurement and moving range control charts for when the heating cycle is off and when the heating cycle is on. So not terribly difficult things to do interactively, but if these were data you were pulling from a database on a daily or weekly basis, it would be really nice to be able to automate this process of finding those minimum and maximum temperatures and pulling them out and getting your control charts.
