The Role of Automated Computer Vision Systems in Industry
Computer vision systems have been used throughout the manufacturing industry for some time, but with the addition of modern sensors and emerging Artificial Intelligence (AI) technologies, today’s automated vision systems are finding their way into more applications and helping to optimize operations throughout industrial facilities. This blog will introduce the latest in automated vision technologies, explain why you should consider using them and highlight potential applications.
What is Automated Computer Vision?
Automated computer vision, also known as automated machine vision, is a form of Artificial Intelligence (AI) that allows computers to capture, understand and analyze visual data in a way that is similar to human vision, but provides higher levels of efficiency, accuracy, effectiveness and consistency. Computer vision systems rely on the use of cameras and sophisticated algorithms to capture, process and interpret visual data, as follows:
- Image Capture: Computer vision systems capture images or videos using cameras or imaging devices.
- Image Enhancement: This image or video is then filtered and resized to enhance quality and remove any noise and unimportant details.
- Feature Extraction: Relevant features and details from the enhanced images are then extracted using computer vision algorithms.
- Object Recognition: By comparing the extracted features to programmed models or patterns, the objects contained in the images are recognized, classified and tracked.
- Analysis: Once these meaningful objects are identified, they are analyzed for unusual attributes, behaviors or patterns. Any anomalies are flagged to enable proactive decision making based on the visual data.
These components work together to create an automated computer vision system that can enhance industrial equipment by providing it with the ability to “see” what is happening and make real-time, information-based decisions about the next action based on the images and data that it collects and interprets. This means that computer vision systems are well suited for image-based inspection and detection tasks, as well as other surprising applications in industrial, manufacturing and packaging operations. While these activities can be done manually, computer vision-enabled equipment can perform tasks faster and more accurately than humans, boosting efficiency and quality and promoting proactive action, while reducing operational costs.
Why Use Computer Vision Systems?
Computer vision systems excel at fast, accurate and repeatable quantitative analysis of a structured scene, which means it can successfully perform tasks such as inspection, measurement, defect detection and monitoring at extremely high counts per minute, increasing quality and efficiency in these types of applications.
Further, because cameras are used for visual inspections, rather than traditional test equipment, the use of computer vision prevents damage to products, parts and packages, further enhancing quality and lessening scrap and waste. In addition, by cutting down on human involvement in industrial applications and around fast-moving machinery it reduces potential injuries. And, if it is applied in cleanroom areas, the use of automated computer vision versus manual labor minimizes the risk of contamination.
Additionally, if automated computer vision is applied to certain areas or machines and the data is monitored and analyzed, it can be used for proactive maintenance planning and facility security, while reducing downtime and protecting assets.
The Role of Computer Vision in Industry
There are hundreds of applications for automated computer vision in manufacturing and industry. Among them are:
|Inspection||Automated computer vision can be used in a wide variety of inspection, defect detection and quality control operations, including: identifying incorrect or damaged labels on products and packages; detecting product, packaging or surface defects such as dents, broken parts, missing parts and deformities; inspecting packages for damage or holes, wrinkled labels, incorrect dates or codes; and detecting missing caps, lids or seals. Identifying defective products or packages improves quality control for manufacturers and packagers, potentially preventing the cost and labor associated with rework and avoiding loss of business.|
|Process Control||Because automated computer vision systems collect data in real time, the feedback can be used to better control robot or equipment positioning and operation, as well as the process itself, while also monitoring for events. If issues are detected, users can be alerted so they can proactively make informed, data-based corrective actions before the process goes askew. Detecting anomalies in the process or with equipment can prevent wasted raw materials and scrapped finished product, while boosting product quality and ensuring that the process remains up and running within specifications.|
|Tolerance Measurement||Similar to inspection applications, automated computer vision systems can verify part tolerance, thread counts, part measurements and compare finished parts to CAD images to ensure production of high quality parts that meet specifications.|
|Asset Management and Security||As automated computer vision can detect patterns of behavior, identify people and survey areas, it can detect when people enter off-limits areas in facilities and send alerts if assets are removed from storage locations. This can also be employed in warehouse and logistics operations to increase security and decrease theft along the supply chain, ensuring that packages and products arrive in the right location, while also continuing to monitor the condition of packaging and detect open or damaged product before it reaches its destination.|
|Safety Enhancements||Machines equipped with automated computer vision enhance safety in several ways. First, minimizing human contact with fast moving equipment prevents injuries. Second, because computer vision can be used to survey areas and interpret human actions and behavior patterns, users can be alerted or equipment can be programmed to stop when workers enter a dangerous area or are too close to machinery, reducing the risk of an accident or entry into hazardous locations.|
|Machine Anomaly Detection||Because automated computer vision systems can collect and analyze data about the process, machinery or the surrounding areas, it can be used to detect faults and other signs that equipment maintenance may be required. This means repairs can be proactively scheduled before there is a breakdown, potentially decreasing downtime, throughput losses and maintenance costs.|
By providing image-based, real-time data from inspection, detection and monitoring activities, automated computer vision can be used to proactively improve efficiency, safety, product and package quality and security throughout manufacturing and industrial facilities, helping to slash operational expenses. Because vision technologies continue to advance and evolve, automated computer vision systems will begin to play a more significant role as an effective solution to common manufacturing issues. Reach out to a representative at JHFOSTER to see how automated computer vision can help your facility optimize operations.