Remote Machine-Vision Inspection with Centralized Quality Analytics
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Solution Overview
Problem
Traditional machine-vision systems operate as autonomous cells, limiting data sharing and remote access, requiring local operators for software updates, and lacking comprehensive data management, which impedes uniformity and efficiency in quality inspection across multiple production lines.
Innovation Solution
A machine-vision system that integrates a controller, vision server, and remote terminal over data networks to collect, analyze, and store image data, enabling remote monitoring and control of multiple inspection stations, with expandable storage and dynamic analytics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional autonomous-cell machine-vision systems are used, then each inspection station can operate independently with simple local processing, but data sharing between stations is limited and remote access is not supported
Solution Approach 1:
The patent merges multiple autonomous inspection stations into a unified networked system where controllers communicate with a central vision server through data networks. This allows each station to maintain its independent inspection functionality while simultaneously enabling data sharing, aggregation, and centralized management across all stations, thus resolving the contradiction between operational independence and data sharing capability.
Solution Approach 2:
The vision server provides universal access and control capabilities that serve multiple inspection stations simultaneously. It enables remote monitoring, centralized software updates, and aggregated data analysis across the entire network, allowing a single system to perform functions that were previously requiring multiple separate systems, thereby enhancing adaptability without compromising individual station reliability.
2Reliability
If multiple inspection stations are distributed throughout production lines, then comprehensive quality monitoring is achieved, but physical presence near inspection stations is required for monitoring and maintenance
Solution Approach 1:
The vision server acts as an intermediary between the distributed inspection stations and the user. It receives data from all stations, processes information centrally, and provides remote access to quality metrics and system status. This mediator enables comprehensive quality monitoring across multiple stations while eliminating the need for physical presence at each location, as users can access all information remotely through the server.
3Measurement precision
If high-resolution digital cameras are used for detailed inspection, then measurement precision is improved, but the amount of image data generated increases significantly
Solution Approach 1:
The system extracts only the essential information from high-resolution images by using machine vision algorithms to identify and measure specific features and defects. Rather than storing and processing entire high-resolution images, the vision server extracts key measurements and quality metrics, thereby maintaining measurement precision while significantly reducing the volume of data that needs to be stored and transmitted.
Solution Approach 2:
The inspection system segments the image processing task into two stages: local controllers perform initial image acquisition and basic analysis, then only relevant results and extracted features are transmitted to the vision server. This segmentation allows high-resolution imaging for precise measurement while reducing overall data volume by processing and filtering information at the source before central aggregation.
4Productivity
If each inspection station operates autonomously, then local control is simple and responsive, but configuration updates require physical access and are difficult to standardize
Solution Approach 1:
The vision server enables preliminary configuration and standardization of inspection parameters across all stations before deployment. Configuration files, machine vision algorithms, and quality criteria can be pre-configured centrally and then distributed to all inspection stations through the data network, ensuring uniformity across the system while maintaining local operational autonomy and productivity.
Data Source
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AI summary
A machine-vision system for monitoring a quality metric for a product. The system includes a controller configured to receive a digital image from an image acquisition device. The controller is also configured to analyze the digital image using a first machine-vision algorithm to compute a measurement of the product. The system also includes a vision server connected to the controller, and configured to compute a quality metric and store the digital image and the measurement in a database storage. The system also includes a remote terminal connected to the vision server, and configured to display the digital image and the quality metric on the remote terminal.