CAD Environmental Modeling for Additive Manufacturing Fit
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Solution Overview
Problem
CAD modeling for rapid prototyping is inefficient due to time-consuming and error-prone dimensioning of customized models, especially when fitting into existing systems or environments, as users lack the ability to simulate the interaction of the customized model, leading to potential unforeseen interferences.
Innovation Solution
A computer-implemented method using augmented reality mapping techniques to extract contextual information from images of a physical area, replicating the environment in a CAD workspace, allowing for accurate modeling and fabrication of objects with relative sizing and positioning, and generating print files for additive manufacturing, including orientation instructions for precise placement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If users manually measure and approximate dimensions for customized models, then the modeling process can be completed, but the process becomes time-consuming and error-prone
Solution Approach 1:
The patent performs preliminary actions by capturing images of the physical environment and pre-extracting spatial information (coordinates, dimensions, relationships) before the actual CAD modeling begins. This pre-processing of environmental data eliminates the need for manual measurement during the modeling phase, directly improving productivity while reducing time loss.
Solution Approach 2:
The patent creates a digital copy of the physical environment by replicating spatial relationships, object positions, and dimensional data from real-world images into a virtual CAD workspace. This copying approach replaces manual measurement and approximation with automated data transfer, significantly reducing both time consumption and errors in dimensioning.
2Measurement precision
If users approximate dimensions without simulating interactions, then modeling can proceed quickly, but unforeseen interferences and errors increase
Solution Approach 1:
The patent performs preliminary simulation by placing the customized model into the replicated virtual environment and testing its interactions with existing objects before finalizing the design. This preliminary validation identifies potential interferences and dimensional mismatches early, ensuring both measurement precision and reliability of the final fit in the physical environment.
Solution Approach 2:
The patent implements feedback mechanisms by continuously comparing the customized model's position and dimensions against the replicated environmental constraints during the modeling process. This real-time feedback ensures that the model maintains accurate dimensional relationships with surrounding objects, preventing errors and ensuring reliable fit in the actual physical environment.
3Adaptability or versatility
If environmental data is not integrated into CAD workspace, then the modeling process is simpler, but the ability to ensure proper placement and fit is reduced
Solution Approach 1:
The patent copies essential environmental data (spatial coordinates, object positions, dimensional relationships) from the physical environment into the CAD workspace, creating a virtual replica that guides the customization process. This copying approach enhances adaptability by providing accurate environmental context while managing complexity through automated data extraction and structured integration of the replicated environment into the CAD system.
Data Source
AI summary
Described are techniques for infusing environmental data into a Computer-Aided Design (CAD) workspace. The techniques include replicating a physical area in a CAD workspace, where a static object of the physical area is replicated in the CAD workspace with a single set of coordinates, and where a dynamic object of the physical area is replicated in the CAD workspace with a range of coordinates representing movement. The techniques further include using the CAD workspace to enable relative sizing of a modeled object in the CAD workspace, where the relative sizing is relative to the single set of coordinates associated with the static object and the range of coordinates associated with the dynamic object.