AI-Guided Fixtureless Part Joining for Flexible Sheet Metal Assembly
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Solution Overview
Problem
The high costs and obsolescence of dedicated hardware fixtures in manufacturing, particularly in the automobile industry, due to the complexity of design and frequent product changes, necessitate a more flexible and cost-effective solution for securing and joining sheet metal parts.
Innovation Solution
A reconfigurable, fixtureless manufacturing system utilizing learning AI software and material handling robots with machine vision systems to align and join parts without physical fixtures, allowing for the use of virtual datums and adaptation to various part shapes and sizes through iterative learning algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If dedicated hardware fixtures are used to secure and locate sheet metal parts for welding, then manufacturing precision and reliability are improved, but device complexity and manufacturing costs increase significantly
Solution Approach 1:
The patent uses machine vision systems to create virtual copies (digital models) of physical fixtures and parts. These virtual fixtures serve as references for positioning and alignment, eliminating the need for complex physical fixtures while maintaining positioning accuracy through optical field replication.
Solution Approach 2:
The patent replaces mechanical positioning systems (physical fixtures) with optical and computational systems. Machine vision captures part positions, and software algorithms calculate optimal positioning, substituting mechanical complexity with optical sensing and computational processing.
2Manufacturing precision
If dedicated hardware fixtures are designed for each subassembly, then manufacturing precision is maintained, but adaptability to product changes deteriorates
Solution Approach 1:
The patent implements dynamic, reconfigurable fixture systems that can adapt to different products. Physical fixtures are made adjustable and reconfigurable through mechanical modifications, allowing the same fixture system to accommodate various product designs while maintaining assembly accuracy.
Solution Approach 2:
The patent changes key parameters of fixtures (position, orientation, geometry) based on product requirements. By making fixture parameters adjustable rather than fixed, the system can adapt to different subassemblies and product configurations while preserving manufacturing precision through controlled parameter modification.
3Adaptability or versatility
If flexible fixture systems are used to accommodate product changes, then adaptability is improved, but device complexity and manufacturing costs increase
Solution Approach 1:
The patent uses virtual fixtures (digital models) to replace complex physical flexible fixtures. The virtual fixtures provide the necessary adaptability through software reconfiguration rather than mechanical redesign, significantly reducing the complexity of the physical fixture system while maintaining reconfigurability.
Solution Approach 2:
The patent extracts the essential positioning and alignment functions from complex flexible fixtures and implements them through machine vision and software algorithms. This separation removes unnecessary mechanical complexity while retaining the adaptability needed for product changes.
4Productivity
If robots and automated assembly systems with physical fixtures are used, then productivity is improved, but adaptability to new products deteriorates due to fixture obsolescence
Solution Approach 1:
The patent replaces fixed mechanical fixtures in automated assembly systems with vision-based virtual fixtures. This substitution allows robotic systems to maintain high productivity through automation while gaining adaptability, as the virtual fixtures can be reconfigured through software for new products without hardware changes.
Solution Approach 2:
The patent makes the automated assembly system dynamic by enabling real-time reconfiguration of virtual fixtures based on product requirements. This allows the robotic system to adapt to different product lines while maintaining automated productivity, eliminating the obsolescence issue associated with fixed physical fixtures.
Data Source
AI summary
Systems and methods for automated manufacture are provided. User input is received by way of user systems indicating nominal data measurements for an article. Automated material handling machines move parts within view of a machine vision system which performs an initial scan to identify features of said parts. Locations of areas for joining are determined by comparing the identified features to the nominal data measurements and the automated material handling machines move the parts into positions in accordance with the nominal data measurements to form the article. The automated material joining machines join the parts at said areas specified in said user input to form the article.