How Computer Vision in Manufacturing Automation Is Changing the Industry

Computer vision is the subset of AI that processes and understands the input provided by images and video. While many companies in the industry are already leveraging robotic process automation in manufacturing, the introduction of computer vision has uncovered more potential applications that will further revolutionize the manufacturing sector.

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It’s no surprise that the market valuation for AI in manufacturing (which includes computer vision) is expected to surge from US$1.48 million in 2021 to a whopping US$17.9 million by 2028. Where is this unprecedented growth coming from? Here are the some of the latest AI and computer vision use cases:

• Quality Inspection and Control. Computer vision technology is proving to be very useful when it comes to automating quality inspection during the production process. This holds a lot of value in the manufacturing sector where quality standards should be maintained at all times. Using manufacturing machine learning and computer vision algorithms, quality control and inspection tasks are maintained at a high level of accuracy with minimal human intervention.

• Supply Chain Optimization. Ensuring that there are no breakdowns in the supply chain is an important part of production. An optimized supply chain guarantees efficiency in the production and distribution, and boosts customer satisfaction. While many tasks in the supply chain optimization previously required human control, these can now be done using systems designed for computer vision manufacturing automation. Drone systems, for example, can perform tasks like warehouse management and inventory management, where real time camera streams can detect empty containers and indicate the need for restocking.

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• 3D Vision Monitoring. In 3D vision monitoring, the AI system uses high-resolution images to build a highly-accurate production process model complete with components and connector pins. When any detail of the model bears faulty threading or deviates from the standard design, the system can trigger an alarm to the engineer to prevent flaws and/or malfunctioning. This technology is commonly used in sectors like automotive, electronics, oil and gas, and others.

• Enhanced Safety Measures for Workers and Equipment. Safety is an essential component in production floors because employees are working with equipment and are susceptible to accidents. Applying computer vision in the manufacturing process has improved safety conditions by doing away with the traditional manual monitoring of workers using surveillance cameras. Instead, computer vision systems deploy an object tracker that constantly monitors all areas of the manufacturing site, particularly the entry and exit points. When suspicious items or people are moving in a monitored location, alerts are sent to the concerned personnel in charge.

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Machines have now gained the capability to match or even outperform humans in certain work activities — even those that demand some degree of cognitive abilities, and this will create many dynamic changes in production automation. Enterprises can discover more value in manufacturing process automation in this era of Industry 4.0 (the next revolution in manufacturing), where AI, machine learning, and computer vision take center stage.

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