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Product Engineering Optimizer By: Jared Garrison, Jason Brubaker, and Justin Magleby

Product Engineering Optimizer By: Jared Garrison, Jason Brubaker, and Justin Magleby

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Optimizer Setup: Formulas can be entered to define aspects of a part CATIA will vary the free variables and select the best permutation Constraints help to set the ranges for the parameters to keep the design feasible

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Page 1: Product Engineering Optimizer By: Jared Garrison, Jason Brubaker, and Justin Magleby

Product Engineering Optimizer

By: Jared Garrison, Jason Brubaker, and Justin Magleby

Page 2: Product Engineering Optimizer By: Jared Garrison, Jason Brubaker, and Justin Magleby

Problem

• I-Beam Optimization– Fixed weight – Fixed length

• Parameters to optimize for minimizing deflection:– Height– Width– Web & Flange thickness

Page 3: Product Engineering Optimizer By: Jared Garrison, Jason Brubaker, and Justin Magleby

Optimizer Setup:

Formulas can be entered to define aspects of a part

CATIA will vary the free variables and select the best permutation

Constraints help to set the ranges for the parameters to keep the design feasible

Page 4: Product Engineering Optimizer By: Jared Garrison, Jason Brubaker, and Justin Magleby

Optimizer Output:CATIA creates an excel document consisting of all of the iterations that it made during its analysis

Page 5: Product Engineering Optimizer By: Jared Garrison, Jason Brubaker, and Justin Magleby

Before Optimization:

After Optimization:

Inertia = 4.557e-005 m^4

Inertia = 6.45e-005 m^4

Page 6: Product Engineering Optimizer By: Jared Garrison, Jason Brubaker, and Justin Magleby

Possible Future Experiments• Experimentation with the “only constraints” optimization.

• Cost analysis of optimizations, either in CATIA, or excel.

• Optimizing to minimize required welding or machining.

• Using the optimizer to improve the design of assemblies.

• Including constraints to allow for tool and fastener clearances.