MCAD Modeling Methods: Design Optimization15 Aug, 2004 By: Don LaCourse
MCAD tools help explore design options and improve systems.
MY TIME AS A PRODUCT designer began at about the same time that the first 80386 16-bit PCs ran the earliest versions of AutoCAD.
As a young board designer, I relished in the newfound freedom that AutoCAD provided. No more redrawing old designs to make new ones. No more hand lettering and no more messy ink on mylar film. I remember the time I drew my last GD&T symbol.
Figure 1. Using the 3D Design Optimizer included in VX CAD/CAM v10, you can automatically drive dimension parameters to achieve a target parameter, such as volume.
Optimization for part and systems design in today's mechanical CAD applications breaks similar ground by relieving designers from the burden of examining multiple iterations of a part to achieve a desired specification and to perform systems-level problem solving. Good examples of this are VX CAD/CAM's 3D Design Optimizer (figure 1) and CATIA's Product Function Optimizer.
Figure 2. When you check the dimension variables BottleHeight and BottleWidth in the dialog box, the program automatically performs multiple design iterations and stops when it achieves the target volume-2,000 cubic centimeters in this example.
Part Design OptimizationWith VX CAD/CAM's 3D Design Optimizer, you can optimize a part to achieve a desired target parameter. For example, you can change the design of a bottle to achieve a certain volume. The command dialog box lets you define several driving variables and dimensions along with a target variable. When you run the command, VX automatically modifies the driving dimensions and variables to minimize or maximize the value of the target variable or to drive it toward your specified value.
The command automatically tweaks the driving dimension variables and regenerates the part. This is considered one iteration. It automatically performs multiple iterations and stops when it achieves the target parameter. There are +/- buttons and a step size value so that you can interactively change dimensions to drive the target variable up or down. You can also step through the design optimization one iteration at a time and save the optimization setup with the active part. It automatically is recalled the next time you invoke the command.
Figure 3. Here the bottle is again optimized to achieve a desired volume of 2,000 cubic centimeters, only this time the bottles height changes and the width stays the same.
Figure 2 shows the command modifying the bottle design in figure 1 to achieve a target volume of 2,000 cubic centimeters. During the optimization, both driving dimension variables are adjusted. Figure 3 shows the command optimizing the bottle by changing the height and constraining the width to its current value. You can perform what-if scenarios by checking the dimensions to adjust and unchecking those that should not change.
Systems Design OptimizationAt the conceptual stage of development, CATIA's PFO (Product Function Optimizer) helps you detect engineering problems by creating functional systems for a product and providing helpful methods and knowledge databases to solve problems (figures 4-6).
To accomplish this, PFO uses Invention Machine Corp.'s (www.invention-machine.com )TechOptimizer design kernel knowledge to add expertise in functional system modeling to the CATIA portfolio. PFO helps you numerically diagnose the value of systems and offers strategies to improve this value. PFO identifies and categorizes functional problems in a system and helps you solve them by searching for solutions in dedicated knowledge databases.
With PFO, you identify functional objects involved in the product (seen as a system) and the interactions between them. The system is presented as a graph in which objects are displayed as nodes and their interactions as arcs. This results in a graphical presentation of sentences. You define the semantic view of the product before preliminary and detailed product design stages.
Figure 4. Dassault Systèmes CATIA graphs the impact of a parameter. The three curves represent the mean effect of the parameter on the output, and the minimum and maximum effects.
Design Optimization Wrap-upFrom part design to system design, mechanical applications today take a heavy load off designers' backs by allowing them to explore options and solve system problems in the early stages of a product's design. This sort of design optimization technology makes today's mechanical CAD applications more than a replacement for the drawing board.
Figure 5 (above). Using CATIA, you can define the relationships and the functional behaviors of the system, as with this windshield wiper system schematic.
Figure 6 (left). CATIA lets you view optimum possible shapes based on a parameter.
Thanks to VX Corp. and Dassault Syst笥s for supplying information and images for this month's column.