Weaknesses in the CAD structure rarely become apparent right away in day-to-day operations. A model works, a drawing is generated, and the project moves forward. It’s only when production begins and changes have to be rolled out across the entire structure that it becomes clear just how costly even minor oversights can be.
The most common causes
In our consulting practice with Siemens Designcenter NX and Teamcenter, we repeatedly encounter the same three patterns:
Unclear Feature Sequences: If design steps are not structured in a logical manner, any subsequent change becomes a risk – minor adjustments can trigger unexpected errors in completely different parts of the model.
Inconsistent naming conventions: Without standardized naming conventions, the structure becomes difficult to read for anyone other than the person who created it. This wastes time during onboarding, debugging, and team collaboration.
Unstable reference geometries: If features are not referenced robustly enough, even a small geometric adjustment is often enough to trigger cascading errors throughout the entire assembly – resulting in significant effort to fix them.
Taken individually, these points often seem harmless. Taken together, however, and across many components, they lead to precisely the kinds of change risks that become particularly costly during the start of series production.
What a CAD structure audit does
In a concise audit, we take a structured look at your existing Siemens Designcenter NX models or Teamcenter structures. The result is not generic feedback, but a prioritized list of specific areas to address: Where exactly are the greatest risks, which adjustments will have the greatest impact, and where should you start?
This provides clarity before a messy structure turns into a real problem in the project.
Where your CAD structure stands today
Would you like to know how your own models and structures are faring? As a PLM consulting firm specializing in Siemens Designcenter NX and Teamcenter, we help you identify weaknesses early on and address them effectively – from the initial assessment to an AI-ready PLM architecture.
Feel free to contact us with no obligation: