Automated Shoe Part Assembly Using Image-Guided Recognition
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Solution Overview
Problem
Traditional shoe manufacturing methods are resource-intensive and prone to high variability due to reliance on manual execution, leading to inefficiencies and inconsistencies in the assembly of shoe parts.
Innovation Solution
An automated manufacturing system that utilizes a part-recognition system to analyze images of shoe parts, determining their identity, orientation, and surface topography, and instructs manufacturing tools for precise pickup, transfer, and attachment processes, enabling automated assembly of shoe parts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual execution is used for shoe manufacturing assembly steps, then operational flexibility is maintained, but resource consumption increases and variability is high
Solution Approach 1:
The patent replaces manual mechanical assembly operations with an automated manufacturing system that uses image-guided robotic manipulation. The system captures images of shoe parts, processes them to determine part identities and orientations, and automatically positions parts using robotic tools, thereby eliminating manual execution while maintaining precision and reducing resource consumption.
Solution Approach 2:
The manufacturing system performs self-guided assembly by automatically capturing images of shoe parts, processing the images to determine part characteristics, and using this information to autonomously position and assemble parts without human intervention. The system serves itself by integrating sensing, decision-making, and actuation into a closed-loop automated process.
2Manufacturing precision
If manual execution is used for shoe manufacturing, then adaptability to part variations is maintained, but variability in assembly quality increases
Solution Approach 1:
The patent replaces manual visual inspection and positioning with an automated image-based recognition system. The system captures images of shoe parts, processes them to determine part identities, orientations, and positions, and uses this information to guide robotic assembly tools, thereby achieving precise assembly without manual intervention.
Solution Approach 2:
The system creates a digital representation (image) of the physical shoe part and processes this copy to determine part characteristics. By working with the image data rather than directly manipulating the physical part for identification, the system achieves precise measurement and positioning while simplifying the interaction between the manufacturing system and the part variations.
3Productivity
If automated manufacturing apparatus is used, then productivity and consistency are improved, but initial system complexity increases
Solution Approach 1:
The automated manufacturing system is divided into distinct functional modules: an image capture module that captures images of shoe parts, an image processing module that determines part identities and orientations, and an automated manipulation module that positions parts. This segmentation allows each module to be optimized independently while working together to achieve high productivity and consistency.
Data Source
AI summary
Manufacturing of a shoe or a portion of a shoe is enhanced by executing various shoe-manufacturing processes in an automated fashion. For example, information describing a shoe part may be determined, such as an identification, an orientation, a color, a surface topography, an alignment, a size, etc. Based on the information describing the shoe part, automated shoe-manufacturing apparatuses may be instructed to apply various shoe-manufacturing processes to the shoe part.