AI Driven Generative Design Workflow for Optimal Results

Generative Design Iteration Process

1. Define Objectives

1.1 Identify Project Goals

Establish clear objectives for the generative design project, including desired outcomes such as cost reduction, improved performance, or enhanced manufacturability.

1.2 Stakeholder Engagement

Engage with key stakeholders to gather insights and expectations. This may include engineers, designers, and production managers.

2. Data Collection

2.1 Gather Input Data

Collect relevant data such as material properties, manufacturing constraints, and performance requirements.

2.2 Utilize AI-Driven Tools

Implement AI tools such as Autodesk Fusion 360 or Siemens NX to automate data gathering and ensure comprehensive input.

3. Initial Design Generation

3.1 Run Generative Design Algorithms

Utilize generative design software to create multiple design alternatives based on the input data.

3.2 AI Analysis

Employ AI algorithms to analyze generated designs for feasibility and performance metrics. Tools like Altair Inspire can be used for simulation and optimization.

4. Design Evaluation

4.1 Performance Assessment

Evaluate the designs against predefined criteria such as strength, weight, and cost.

4.2 Feedback Loop

Incorporate feedback from stakeholders to refine design criteria and ensure alignment with project goals.

5. Iterative Refinement

5.1 Select Top Designs

Identify the most promising design alternatives for further development.

5.2 Re-run Generative Design

Utilize AI tools to further iterate on selected designs based on feedback and performance data.

6. Prototyping and Testing

6.1 Create Prototypes

Utilize additive manufacturing technologies, such as 3D printing, to create prototypes of the top designs.

6.2 Conduct Testing

Perform rigorous testing on prototypes to validate performance against requirements.

7. Final Design Selection

7.1 Analyze Test Results

Review testing outcomes and make necessary adjustments to the design.

7.2 Final Decision

Make a final decision on the design to be put into production, ensuring all stakeholder requirements are met.

8. Implementation and Monitoring

8.1 Production Planning

Develop a comprehensive production plan incorporating the final design specifications.

8.2 Continuous Improvement

Implement AI monitoring tools, such as GE Digital’s Predix, to track production performance and identify areas for ongoing improvement.