Oct. 18, 2024
Food and Beverage: AI Adds New Layers of Flexibility to Vision-Guided Robotics
For decades, the combination of machine vision systems and robots have been paired together to solve a wide range of pick and place applications, from automotive plants to the warehouse floor. In food and beverage manufacturing, new challenges emerge due to the variability in products, especially with organic products like protein or produce. Introducing AI-enabled vision into robotic solutions transforms vision-guided robot solutions into adaptive, efficient systems that can handle the high variability challenges inherent in food and beverage automation. This article looks at the ways that AI, machine vision, and robots work in tandem to keep pace with evolving needs of today’s food and beverage companies worldwide, while providing real-world problem/solution examples.
Key Technologies: Vision-Guided Robotics, AI, machine vision
GigE Vision 3.0 Pushes Imaging Technology to New Heights
If image cameras and sensors cannot communicate smoothly with frame grabbers or industrial computers, modern machine vision applications fall apart. Hardware manufacturers cannot solve these problems alone. It takes the entire machine vision community, working through organizations such as the Association for Advancing Automation (A3) and its technical committees to develop standardized solutions that empower the best use of machine vision technology. Currently, by leveraging RDMA over Converged Ethernet (RoCE) technology, A3 is setting the stage for another innovation that stands to influence the entire industry: the impending release of GigE (Gigabit Ethernet) Vision 3.0. The newest upgrade to the quintessential GigE Vision interface will make data transfer faster than ever before, enable superior error detection efficiency, and increase real-time processing and decision-making speeds.
Key Technologies: RDMA, machine vision, vision system components
Thermal Vision for Industrial Inspection
Falling prices, rising resolutions, better algorithms, and a need for less cooling are expanding the use of thermal imaging in industrial inspection applications. Spotting defects in aluminum seals on bottles or poor welds between plastic and metal are example applications where these innovations are leading to use cases that were not feasible a few years ago. But there’s still a need for specialized expertise, such as knowing that aluminum has a low emissivity and how to handle what can be large heat sources in an industrial application. A look at examples reveals the current state-of-the art and where things are headed.
Key Technologies: thermal imaging
Download Media Planner