The safety factor above target visualization focuses exclusively on areas where the safety factor exceeds your upper threshold (default: > 4.0). This visualization highlights over-engineered regions where you might reduce material, weight, or cost without compromising safety. Areas at or below the threshold are hidden from view, allowing you to focus on optimization opportunities.

This focused view is especially useful during design optimization when you're trying to reduce weight or cost while maintaining adequate safety margins.

Things to look for

The Above Target visualization helps you identify and evaluate optimization opportunities:

• Most over-engineered regions (darkest blue): Areas with the highest safety factors indicate maximum potential for weight or cost reduction. These regions have significant excess material that could be removed.

• Moderate over-engineering (medium blue): Areas with safety factors moderately above the threshold offer opportunities for material reduction with careful design changes.

• Areas just above threshold (lightest blue): Regions where safety factors are only slightly above the upper threshold. Optimize these areas carefully to avoid creating new critical areas.

• Design efficiency balance: While high safety factors indicate a robust design, excessive safety factors suggest inefficiency:

  • Material costs more than necessary
  • Parts weigh more than required
  • Manufacturing may be more complex or expensive than needed

Use this visualization to find the balance between safety and efficiency while maintaining adequate safety margins based on your industry requirements and application.

Using this result

Use the threshold slider on the legend to explore over-engineered areas and identify optimization opportunities:

• Drag the slider downward to expand the view to include areas closer to the threshold
• Drag the slider upward to focus only on the most over-engineered regions
• Click on the model to see the exact safety factor value at specific locations
• Read the legend to understand the current range being displayed

The visualization helps you prioritize optimization efforts:

• Darkest blue areas: Highest safety factors indicate the most over-engineered regions with maximum weight reduction potential
• Medium blue areas: Moderate over-engineering with opportunities for material reduction
• Light blue areas: Safety factors just above threshold; optimize carefully to avoid creating critical areas

When making design changes based on this visualization:

1. Start with the darkest blue areas for maximum weight/cost savings
2. Make incremental changes and re-run the simulation
3. Switch to Traffic Light Plot to verify no new critical areas have emerged
4. Use Below Target visualization to confirm all areas remain above the lower threshold

Next steps

Based on the over-engineered areas identified in Above Target visualization:

Reduce material:

• Decrease wall thickness in the darkest blue regions to remove excess material
• Add lightening features such as pockets, cutouts, or lattice structures in thick sections
• Simplify geometry by removing unnecessary reinforcements, bosses, or gussets
• Create hollow sections where solid material provides excessive strength

Optimize materials:

• Substitute lighter materials (e.g., aluminum instead of steel) in over-engineered regions while maintaining adequate strength
• Use composite materials in areas where high safety factors allow for material property trade-offs

Iterative optimization workflow:

1. Identify the darkest blue areas as primary optimization targets
2. Make incremental design changes to reduce material
3. Re-run the simulation to verify safety factors remain acceptable
4. Switch to Traffic Light Plot to ensure no red areas have emerged
5. Use Below Target visualization to confirm all areas stay above the lower threshold (default: 2.0)
6. Repeat until achieving desired balance between safety and efficiency

Design validation:

• Always maintain adequate safety margins based on your industry standards
• Consider dynamic loads, fatigue, material reliability, and failure consequences
• Verify that cost or weight savings justify the engineering effort for optimization