Vision-Based Workpiece Tracking for Automated Sewing Quality Control
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Solution Overview
Problem
Automated sewn product manufacturing systems face challenges in accurately tracking and determining the location of workpieces within the sewing robot work area, which hinders the ability to ensure proper processing and quality control.
Innovation Solution
A vision system comprising a processor, sensors, and modules for incoming inspection, inline processing, and quality inspection, which captures and compares sensor data with precomputed profiles to determine workpiece position and quality, enabling corrective actions and maintaining processing within specified guidelines.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated sewn product manufacturing systems are implemented, then productivity is improved, but the ability to accurately track and determine workpiece location deteriorates
Solution Approach 1:
The patent introduces vision systems and sensor arrays as intermediary devices between the automated sewing robot and the workpiece. These sensors capture images and data about workpiece location, fabric tension, and stitching quality, enabling the automated system to accurately track and determine workpiece position without manual intervention. The sensor data serves as a mediator that bridges the gap between automation and precise measurement.
Solution Approach 2:
The patent replaces mechanical tracking methods with optical and electronic sensing systems. Instead of using physical markers or mechanical guides on the fabric, the system uses vision systems with cameras and sensors to detect workpiece location, fabric edges, and stitching parameters. This substitution enables accurate tracking in automated systems without adding mechanical complexity to the sewing process.
2Measurement precision
If vision systems and sensors are added to track workpieces, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent designs the vision system and sensor array to perform multiple functions simultaneously. The same camera system used for workpiece location tracking also monitors fabric tension, detects stitching quality, and guides the sewing robot. This multi-functionality reduces the need for separate specialized devices for each measurement task, thereby limiting the increase in device complexity while maintaining high measurement precision.
Solution Approach 2:
The vision system and sensors are integrated directly into the sewing robot apparatus, allowing the system to self-monitor and self-adjust during operation. The sensors automatically capture workpiece position data and feed it back to the control system, which adjusts stitching parameters in real-time without requiring external monitoring equipment or complex external control systems.
Data Source
AI summary
Due to rapid advancement in computing technology of both hardware and software, the labor intensive sewing process has been transformed into a technology-intensive automated process. During an automated process, processing of a work piece can be visually monitored using a sensor system. Data gathered from the sensor system can be used to infer the condition and/or position of the work piece in the work area using, e.g., models of a sensor profile. Evaluation can be carried out before processing begins, during processing and/or after processing of the work piece. Examples of systems and methods are described that provide for initially and successively matching the model of the expected shape for a product work piece to a set of sensor readings of the work piece in order to determine the position of the work piece and support a variety of useful features.