Total Number of Pages: 330
Total Hours: 16
The CATIA V5-6R2018: Functional Tolerancing & Annotation learning guide has numerous practices that will help you acquire the skills to create and display engineering, manufacturing, and assembly information directly on the 3D part, assembly, or process model. This extensive hands-on course will provide you with a thorough understanding of geometric tolerances, dimensions, notes, and other annotations critical to the accurate and cost-effective creation of mechanical parts and assemblies. The 3D Functional Tolerancing & Annotation course complies with the industry and government initiated American Society of Mechanical Engineers’ (ASME) Y14.41 3D standards for the creation and submission of model only, paperless design applications.
Topics Covered
- Introduction to Functional Tolerancing & Annotation
- Workbench overview
- Annotation process
- Extracting 2D view from the 3D model
- Annotation planes and extraction views
- Construction geometry
- Semantic and non-semantic annotations
- Datum Reference Frames
- Tolerance Advisor
- Basic Dimensions
- Annotations: Text, Flag Notes, Datum Elements, Datum Targets, Roughness, Dimensions
- Restricted Areas
- Threads
- Annotation Visualization Tools: Query, Grouping, Leader Symbols, Annotation
- Mirror and Transfer, Filters
- Cameras and Captures
- Geometry Connection Management
- FT&A analysis and reporting
- Product Functional Tolerance and Annotation workbench
Prerequisites
- Access to the V5-6R2018 version of the software, to ensure compatibility with this guide. Future software updates that are released by Dassault Systèmes may include changes that are not reflected in this guide. The practices and files included with this guide might not be compatible with prior versions (i.e., V5-6R2017).
- Working knowledge of GD&T application and completion of CATIA V5-6R2018: Introduction to Modeling course are recommended.
Course material includes access to practice files.
Printed guides are coil bound and printed in black and white with images in grayscale.