4: AI and AM Generative Design

Last updated

Mar 18, 2025
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- 3: Additive Manufacturing Methods
- 5: Cost Analysis of Traditional Manufacturing vs. Additive Manufacturing Methods

Bryan Guns (Northeast Wisconsin Technical College)
Northeast Wisconsin Technical College

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Figure $\PageIndex{1}$ : AI Generated picture of a generative design motorcycle

Introduction to Generative Design

Generative design is an advanced computational approach that leverages algorithms and artificial intelligence (AI) to explore a vast array of design solutions based on user-defined constraints and objectives. Unlike traditional design methods, where designers manually iterate on a single concept, generative design automates the creation of optimized geometries, often producing organic, lightweight structures that maximize performance. In manufacturing, this technology enhances efficiency, reduces material usage, and enables innovation. Particularly when paired with additive manufacturing (AM). This chapter focuses on implementing generative design within SolidWorks, a widely used computer-aided design (CAD) software, and its applications in modern engineering workflows.

Fundamentals of Generative Design

Generative design operates by defining a design space, specifying boundary conditions, and employing optimization algorithms to generate multiple viable solutions. Key elements include:

Design Goals: Objectives such as minimizing weight, maximizing stiffness, or reducing cost.
Constraints: Physical limits, such as load conditions, mounting points, or manufacturing methods.
Materials: Material properties (e.g., density, yield strength) that influence the outcome.
Manufacturing Method: Specifies whether the part will be produced via AM, machining, or casting, affecting geometric feasibility.

The process typically integrates topology optimization, a subset of generative design, which removes unnecessary material while preserving structural integrity, and more advanced AI-driven exploration for broader design possibilities.

Generative Design in SolidWorks

SolidWorks, offers generative design capabilities through its integration with tools like SolidWorks Simulation and cloud-based platforms such as 3DEXPERIENCE Works. As of 2025, SolidWorks provides a streamlined workflow for generative design via its Topology Optimization Module, accessible within the SolidWorks Simulation add-in. This section outlines the process and tools available.

Workflow in SolidWorks

Model Setup:
- Create a 3D model in SolidWorks, defining the initial design space (the maximum volume the part can occupy).
- Specify preserved regions (e.g., mounting holes, interfaces) that must remain unchanged.
Simulation Setup:
- Access SolidWorks Simulation and define material properties (e.g., aluminum 6061, stainless steel 316L).
- Apply boundary conditions: forces, pressures, or displacements based on real-world use cases.
- Set constraints, such as symmetry or minimum thickness, to align with manufacturing capabilities.
Topology Optimization:
- Select the “Topology Study” tool within SolidWorks Simulation.
- Define the optimization goal (e.g., minimize mass with a stiffness constraint).
- Run the solver, which uses finite element analysis (FEA) to iteratively redistribute material, producing an optimized shape.
Result Evaluation:
- Review the generated design, presented as a mesh or smoothed geometry.
- Validate performance through additional FEA to ensure compliance with engineering requirements.
Refinement and Manufacturing:
- Export the optimized geometry to SolidWorks for final detailing (e.g., adding fillets or adjusting tolerances).
- Prepare the model for manufacturing, typically AM, using SolidWorks’ export tools (e.g., STL or 3MF formats).

Key Features in SolidWorks

Integration with FEA: Seamlessly combines design and analysis, reducing workflow interruptions.
Manufacturing Constraints: Allows users to specify AM overhang angles or machining tool access, ensuring producibility.
Cloud Connectivity: Via 3DEXPERIENCE Works, users can access advanced AI-driven generative design tools beyond basic topology optimization, exploring a broader design space.

Applications in Manufacturing

Generative design in SolidWorks finds applications across industries, particularly when paired with AM:

Aerospace: Lightweight brackets and structural components (e.g., reducing mass by 30% while maintaining load capacity).
Automotive: Optimized suspension arms or engine mounts, balancing strength and weight.
Medical Devices: Custom implants with porous structures for bone integration, tailored to patient anatomy.
Consumer Products: Ergonomic tools or housings with minimal material use.

For example, an aerospace designer might use SolidWorks to design a turbine blade mount, specifying a 50 kN load and a 20% mass reduction goal. The resulting organic geometry, validated through FEA, can be 3D printed using metal laser sintering, achieving performance unattainable with traditional methods.

Advantages of Generative Design in SolidWorks

Efficiency: Automates design exploration, reducing manual iteration time from weeks to hours.
Optimization: Produces lightweight, high-strength parts, critical for cost-sensitive industries.
Integration: Leverages SolidWorks’ robust CAD ecosystem, minimizing software transitions.
Sustainability: Reduces material waste, aligning with eco-friendly manufacturing trends.

Limitations and Challenges

While powerful, generative design in SolidWorks has constraints:

Computational Demand: Requires significant processing power, often necessitating high-end workstations or cloud resources.
Learning Curve: Designers must understand FEA and optimization principles to effectively use the tools.
Manufacturing Dependency: Optimized designs often require AM, which may not suit high-volume production due to cost and speed limitations.

Case Study: Optimizing a Structural Bracket

Consider a structural bracket for an industrial machine, traditionally machined from steel with a mass of 2 kg. Using SolidWorks:

Setup: The designer defines a 10 kN vertical load, fixes two bolt holes, and selects steel (density: 7850 kg/m³).
Optimization: A topology study targets a 40% mass reduction while maintaining a factor of safety of 2.
Outcome: The solver generates a lattice-like structure weighing 1.2 kg, validated via FEA to withstand the load. The design is 3D printed using selective laser melting, reducing material costs by 35% and lead time from two weeks to three days compared to machining.

This example illustrates how SolidWorks bridges generative design and manufacturing, enhancing efficiency and performance

Future Directions

As generative design evolves, SolidWorks is expected to integrate more AI-driven features, such as real-time multi-objective optimization and broader material libraries. Advances in AM technology will further complement these tools, enabling designers to push design boundaries. For students and professionals, mastering generative design in SolidWorks offers a competitive edge in innovative manufacturing.

Conclusion

Generative design in SolidWorks transforms traditional engineering by automating optimization and enabling complex, efficient designs. Its integration with simulation and manufacturing workflows positions it as a vital tool for modern designers.

Picture of SolidWorks Pre-Generative Designed Bracket — Figure $\PageIndex{2}$ : Pictures of SolidWorks Pre-Generative and Generative Designed Bracket

Picture of SolidWorks Generative Designed Bracket — Figure $\PageIndex{2}$ : Pictures of SolidWorks Pre-Generative and Generative Designed Bracket

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Case Study: Optimizing a Structural Bracket

Introduction to Generative Design

Fundamentals of Generative Design

Generative Design in SolidWorks

Workflow in SolidWorks

Key Features in SolidWorks

Applications in Manufacturing

Advantages of Generative Design in SolidWorks

Limitations and Challenges

Case Study: Optimizing a Structural Bracket

Future Directions

Conclusion

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