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Properties for the Optimization Design Study

While analysis helps you simulate a product development cycle on the computer quickly and inexpensively, you still need to create several studies and simulate many scenarios. Each time you make a change, you need to run the analysis and examine the results.

Even in a relatively simple design, you can change several dimensions. Deciding on what combinations to try and the associated bookkeeping and result viewing can become cumbersome.

Design Study exploits the parametric, feature-based modeling, and the automatic regeneration capabilities of the software to automate the optimization process. The software is equipped with a technology that quickly detects trends and identifies the optimum solution in the least number of runs. The program uses a method based on the Design of Experiments.

The program offers two different qualities in the properties of the design study. The software runs a number of trials based on the quality level and the number of variables. For each trial, the program runs all the associated simulation studies with a strategically determined set of variable values. The following table lists the number of iterations for the high quality and fast results methods. The program uses the Box-Behnken quadratic plan for High Quality setting and the the Rechtschafner quadratic plan for the Fast Results setting. Although the Rechtschafner plan performs certain pre-calculations that Box-Behnken design does not require, it needs fewer experiments to form the response function and optimize.

Number of Design Variables High Quality Fast Results
1 3 N/A
2 9 N/A
3 13 N/A
4 25 15
5 41 21
6 49 28
7 57 36
8 N/A 45
9 121 55
10 161 66
11 177 78
12 193 91
13 N/A 105
14 N/A 120
15 N/A 136
16 385 153
17 N/A 171
18 N/A 190
19 N/A 210
20 N/A 231

After running the experiments, the program calculates the optimal design variables by forming a response function relating the goals to the variables and minimizing, maximizing, or satisfying exactly the goals. The program then runs the associated simulation studies to evaluate the results for the optimal design.

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