Machine Vision Inventory Control for Tool Storage Without Sensors
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Solution Overview
Problem
Current inventory control systems for tools in manufacturing and aerospace environments face challenges in accurately tracking the presence and type of tools within storage locations, often relying on costly and prone-to-failure sensors, and lack efficient communication with network systems, leading to inefficiencies and potential tool misplacement or theft.
Innovation Solution
An automated tool control system utilizing machine vision to capture and process images of storage locations, applying visual contrast elements to identify missing or misplaced tools, and integrating with network systems for secure data transfer and multi-factor authentication, enabling efficient tool tracking and management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensors are disposed in each tool storage location to detect tool presence, then inventory determination capability is improved, but device complexity and cost increase significantly
Solution Approach 1:
The system divides the toolbox into multiple storage locations, each with a unique identifier (such as RFID tags, barcodes, or visual markers). Instead of using sensors in each location, the system segments the detection task by having each location self-identify through its unique marker, eliminating the need for active sensing infrastructure.
Solution Approach 2:
The patent uses visual copies or representations of tool identifiers (such as images of RFID tags, barcodes, or colored markers) that can be captured by a camera. The system creates a digital copy of the physical storage location configuration and compares it with captured images to determine tool presence, replacing physical sensors with optical copying and processing.
2Reliability
If manual inventory checks are performed to track tool location, then tool security is improved, but productivity and time efficiency deteriorate
Solution Approach 1:
The system enables self-service inventory monitoring where the toolbox automatically captures images of its contents using an integrated camera, processes the images to identify tools and their locations, and updates inventory status without human intervention. The toolbox serves itself by performing what previously required manual labor.
Solution Approach 2:
The patent replaces manual mechanical inventory checking with an automated optical system. A camera captures images of storage locations, image processing algorithms automatically identify tools and their positions, and the system updates inventory databases electronically, substituting human visual inspection and manual recording with automated vision-based detection.
3Extent of automation
If automated sensor-based inventory systems are implemented, then inventory tracking capability is improved, but reliability decreases due to sensor damage and false alarms
Solution Approach 1:
The system creates visual copies of tool identifiers and storage location configurations through image capture. By comparing digital images with reference data, the system determines tool presence and location without relying on fragile sensors. This optical copying approach is more reliable because images can be stored and compared without degradation.
Solution Approach 2:
The patent uses inexpensive, replaceable visual identifiers (such as colored markers, printed barcodes, or RFID tags) on tools and storage locations. These passive markers are durable, cannot fail electronically, and can be easily replaced if damaged, unlike complex sensor systems that require calibration and maintenance.
4Measurement precision
If visual contrast elements are applied to identify tools in storage locations, then tool identification accuracy is improved, but device complexity increases due to image processing requirements
Solution Approach 1:
The system uses visual contrast elements such as colored markers, colored foam inserts, or color-coded storage locations to identify tools and their positions. The color or visual pattern serves as a unique identifier that can be easily detected by image processing algorithms, providing high identification accuracy through simple visual differentiation.
Solution Approach 2:
The patent employs visual parameters such as color, pattern, or reflectivity differences in storage location markers. These visual parameters are changed or varied to encode location information, allowing the image processing system to distinguish between different storage locations and identify tool positions based on simple visual特征 rather than complex geometric analysis.
Data Source
AI summary
An inventory control system for managing and transporting a subset of tools from a plurality of storage containers. Each of the plurality of storage containers can comprise a plurality of storage locations. Each storage location can store objects, wherein the objects can rest in a tray. Each storage location can comprise at least one image sensing device configured to capture image data of the plurality of storage locations. Each storage location can comprise a data processor configured to receive information representing captured images of the storage locations and data representing the usage or status of the objects associated with the images. The system can further comprise a portable container comprising a plurality of supplemental locations for storing the objects containers. The portable container can be configured to communicate with the plurality of storage locations and configured to reconcile objects shared between the portable container and the plurality of storage containers.