DOE Software for Excel

DOE Software to Fine Tune Your Production Process

Many manufacturing processes and some service processes can benefit from using Design of Experiments (DOE) to optimize their results. Design of Experiments is easy with the right DOE software.

Without DOE software, you're stuck with the world's slowest method for success-trial and error. With Design of Experiments, you just have to test at the high (+) and low (-) values for any particular "design factor" (e.g., pressure, temperature, time, etc.) from your QFD House of Quality, not every increment in between. And you can test more than one factor at a time.

You can make Design of Experiments wildly complex or straightforward and simple. In my first Design of Experiments class we spent an inordinate amount of time understanding "orthogonal arrays" and all of the other "behind the scenes" mathematics, but you don't need to know all of that to conduct a Design of Experiments study - especially if you have good DOE Software.

Manufacturing Example

For simplicity, let's assume you are writing a cookbook and want to find the best directions for baking a cake (which is similar to baking paint on a car finish). To do this, you will want to establish the high-low settings for each "factor" in your study. Let's suppose you have four factors (a four factor experiment):

1. Pan shape: Round (low) vs square (high) pan
2. Ingredients: 2 vs 3 cups of flour
3. Oven temperature: 325 vs 375 degrees
4. Cooking Time: 30 vs 45 minutes

Let's say that you'll rank each resulting cake on a 1-10 scale for overall quality.

You then use the +/- values in the orthogonal array to guide your test of every combination (16 total):

• High: all high values (+ + + + = square pan, 3 cups, 375 degrees, 45 minutes)
• Low: all low values (- - - - = round pan, 2 cups, 325 degrees, 30 minutes)
• In Between: every other combination ("+ + + -", "+ + - -", and so on).

To optimize your results, you might want to run more than one test of each combination. Then you just plug your data into a 16-factor DOE software template (Taguchi or Plackett-Burman format) like the one in the QI Macros and observe the interactions.

Here is a sample QI Macros Plackett Burman DOE software Template:

Design of Experiments software templates for Taguchi 4, 8 and 16 factors and Plackett-Burman are included in the QI Macros for Excel SPC Software.

In Design of Experiments, they talk about "confounding" which simply means that one factor affects another. You'd expect a higher temperature to result in a shorter cooking time, and vice versa, but does a square pan take longer than a round one? Using the results, a Design of Experiments program will draw the interactions between each of the factors as a line graph.

If the two lines are parallel, there's no interaction. Is one end higher than the other? If so, you can immediately tell which value (high/low) gives you the best result.

If the two lines cross, there is an interaction (confounding). And, by looking at where the two lines intersect on the graph, you can determine the optimum settings (e.g., time and temperature) to get the best cake.

To do this using trial-and-error would take hundreds, maybe even thousands of trials, not just 16.

Here are sample charts created by the QI Macros DOE Software.

Service Example:

People who send direct mail rigorously tally their results from each mailing. They will test one headline against another headline, one sales proposition against another, or one list of prospects against another list, but they usually only do one test at a time. What if you can't wait? Using Design of Experiments, you could test all of these factors simultaneously. Design your experiment as follows: