Automated Mechanical Assembly Design via Structured Problem Definition
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Solution Overview
Problem
Conventional computer-aided design (CAD) applications lack tools to facilitate the programmatic generation of mechanical assembly designs, forcing designers to rely on manual and intuitive processes, which are inefficient and prone to lengthy trial-and-error methods due to the lack of structured inputs for design objectives and constraints.
Innovation Solution
A computer-implemented method using a design engine that generates a user interface to capture input data, formalize problem definitions, and apply optimization algorithms to generate a spectrum of design options for mechanical assemblies, automating the design process by transforming ad-hoc design problems into structured inputs for programmatic processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional manual design processes are used, then designers can leverage personal intuition and experience, but the process becomes lengthy and prone to trial-and-error due to lack of programmatic techniques
Solution Approach 1:
The system performs preliminary structuring of design problems by automatically generating problem definitions from partial designs and design criteria before the main design generation process. This preliminary structuring enables programmatic techniques to be applied subsequently, eliminating the need for lengthy manual trial-and-error iterations while preserving designer intent.
Solution Approach 2:
The patent introduces an intermediary problem definition structure that bridges the gap between manual design formulation and programmatic solution generation. This intermediary structure captures design objectives and constraints in a machine-processable format, enabling automated design option generation while maintaining the flexibility of manual design input.
2Adaptability or versatility
If designers formulate design problems mentally, then the process is intuitive and flexible, but no structured inputs are produced which precludes the use of programmatic techniques
Solution Approach 1:
The patent replaces the manual mental formulation process with an automated computer-implemented process. The system automatically generates structured problem definitions from partial designs and design criteria, substituting the need for manual structuring while preserving the flexibility of design formulation through user interface interactions.
Solution Approach 2:
The system performs self-service by automatically generating problem definitions from the information already provided by the designer through the user interface. The computer-implemented method autonomously structures the design problem without requiring additional manual input formatting, enabling seamless integration of programmatic techniques.
3Productivity
If manual trial-and-error design processes are used, then designers can explore design options, but the process is inefficient and lengthy without structured inputs for programmatic processing
Solution Approach 1:
The system performs preliminary structuring of design problems by automatically generating problem definitions from partial designs and design criteria before the main design generation process. This preliminary structuring enables programmatic techniques to be applied subsequently, eliminating the need for lengthy manual trial-and-error iterations while preserving designer intent.
Solution Approach 2:
The patent transforms design parameters from unstructured manual specifications into structured machine-processable inputs. By changing the state of design information from informal to formal structured data, the system enables automated generation of multiple design options, dramatically reducing iteration time while maintaining design exploration capability.
Data Source
AI summary
A design engine automates portions of a mechanical assembly design process. The design engine generates a user interface that exposes tools for capturing input data related to the design problem. Based on the input data, the design engine performs various operations to generate a formalized problem definition that can be processed by a goal-driven optimization algorithm. The goal-driven optimization algorithm generates a spectrum of potential design options. Each design option describes a mechanical assembly representing a potential solution to the design problem.