Product Element Classification for Manufacturing Process Planning
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Solution Overview
Problem
Current design tools like SolidWorks, NX, and Catia cannot automatically determine the mechanical operations required to manufacture product components, leaving a gap in providing necessary manufacturing information for process planning and cost planning.
Innovation Solution
A system and method using feature recognition techniques to identify manufacturing operations such as sheet metal, turn, injection molding, and machining operations, with sheet metal operations having the highest priority, to automate the classification and manufacturing of product elements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If existing modeler tools (SolidWorks, NX, CREO, Catia) are used for designing assemblies, then design capability is improved, but the ability to determine mechanical operations required for manufacturing components is lost
Solution Approach 1:
The system segments the manufacturing information extraction process into distinct feature recognition operations, identifying specific geometric features (cylindrical, spherical, planar, etc.) and mapping them to corresponding manufacturing operations (turning, molding, machining, etc.). This segmentation allows the system to recover manufacturing information that was lost in the design process.
Solution Approach 2:
The patent replaces manual analysis of manufacturing operations with an automated computer-based feature recognition system. The system uses algorithmic processing to identify geometric features and determine manufacturing operations, substituting the mechanical/manual process with an automated computational approach that retrieves manufacturing information directly from design models.
2Manufacturing precision
If manual determination of manufacturing operations is performed, then manufacturing information accuracy is improved, but productivity and automation level deteriorate
Solution Approach 1:
The system enables self-service by allowing the design model itself to provide the manufacturing information. The feature recognition system automatically extracts manufacturing operation data from the geometric features of the design model, eliminating the need for manual intervention while maintaining accuracy. The process plans and cost estimates are generated automatically from the extracted features.
Solution Approach 2:
The system incorporates feedback mechanisms where the recognized features are validated and used to generate manufacturing process plans, which can then be reviewed and refined. The system provides feedback loops that allow verification of the extracted manufacturing information and adjustment of the feature recognition parameters to improve accuracy while maintaining automation.
3Loss of information
If comprehensive feature recognition is implemented to identify all manufacturing operations, then manufacturing information completeness is improved, but system complexity increases
Solution Approach 1:
The system divides the complex feature recognition task into manageable segments, categorizing features into distinct types (cylindrical, spherical, planar, conical, toroidal, etc.) and associating each type with specific manufacturing operations. This segmentation reduces the overall complexity by breaking down the comprehensive recognition task into smaller, more manageable feature categories.
Solution Approach 2:
The system employs a universal feature recognition framework that can handle multiple types of manufacturing operations through a common methodology. The same basic feature recognition algorithms are applied across different feature types and manufacturing processes (turning, molding, machining, sheet metal operations), reducing system complexity through reusability and standardization.
Data Source
AI summary
Disclosed is a method and system for classifying elements of a product. The method comprises identifying elements of the product. Thereupon, features of the one or more elements are determined, using a feature recognition technique. The features correspond to manufacturing operations required for manufacturing the elements, and include sheet metal operations, turn operations, injection moulding operations, and machining operations. The manufacturing operations are determined in a priority order with the sheet metal operation having a highest priority and the machining operation having a least priority.