Computer-Aided Design System for Automated Component Parameterization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Designing complex technical systems is challenging due to the multitude of manufacturers and non-formalized specifications of system components, making it difficult to create formalized planning models.
Innovation Solution
A method involving a computer-aided design system that reads in component names and characteristic parameters, uses a search engine to gather component specifications, and employs a machine learning routine to extract and formalize characteristic parameter values for inclusion in planning data records.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual formalization of component specifications is used, then planning data records can be created, but the process becomes highly time-consuming and complex due to multiple manufacturers and non-formalized specifications
Solution Approach 1:
The patent replaces manual mechanical formalization processes with automated information extraction systems. Machine learning models and natural language processing algorithms automatically extract characteristic parameters from non-formalized component specifications, eliminating the need for manual data entry and formalization while maintaining high precision in parameter extraction.
Solution Approach 2:
The system enables component specifications to self-formalize through automated processing. The machine learning routine automatically parses unstructured specification texts, identifies relevant characteristic parameters, and structures them into standardized planning data records without requiring manual intervention, allowing the system to serve itself in the formalization process.
2Adaptability or versatility
If comprehensive component information is gathered from multiple manufacturers, then optimization margin increases, but information processing complexity and time requirements increase
Solution Approach 1:
The patent implements a universal information extraction framework that handles specifications from multiple manufacturers through a single machine learning model. This multi-functional system can process diverse specification formats, languages, and structures uniformly, enabling comprehensive component information gathering without proportionally increasing processing complexity. The system adapts to different manufacturer formats while maintaining consistent extraction quality.
3Loss of information
If non-formalized component specifications are processed, then more component information becomes available, but automation of planning processes becomes difficult
Solution Approach 1:
The patent replaces manual processing of non-formalized specifications with automated machine learning-based information extraction. The system automatically parses unstructured text, identifies characteristic parameters, and transforms them into structured planning data, enabling full automation of the planning process while preserving complete component information that would otherwise be lost in manual formalization.
Data Source
AI summary
A component of the technical system, a component designation and a characteristic parameter designation for a characteristic parameter of relevance to the design of the components are read and a search engine is queried with same is provided. The documents found by the search engine are read and component information, e.g. product information concerning a specific component, is extracted from said documents. The extracted component information is supplied to a machine learning routine which has been trained, using a plurality of predefined training component information and training characteristic parameter values, to reproduce predefined training characteristic parameter values using predefined training component information. Output data from the machine learning routine is selected as characteristic parameter values and inserted into a planning data record. The planning data record is then output to design the technical system.