Minitab's optimal design capabilities can be used with general full factorial designs, response surface designs, and mixture designs. For more information, go to Overview for Select Optimal Design.
For example, a greenhouse manager wants to use a designed experiment to determine the ideal combination of temperature, light, soil, and water that maximizes the growth of hanging ferns. By using a designed experiment, the manager can evaluate fern growth in response to the various combinations of the factor levels. To do this, the manager creates a response surface design with four factors and two blocks (the blocks represent the two adjacent greenhouses), which results in a design with 30 points (that is, 30 factor level combinations). However, to save money and time, the manager decides to reduce the original design to 20 points, using D-optimality as the criterion to select the best set of design points. The manager can then evaluate fern growth based on only 20 experimental runs.