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Real-Time AI-Based Inspection System Solution Launched

Advantech and Overview have joined forces to offer manufacturers an end-to-end, artificial intelligence (AI) vision inspection solution. Advantech is a leading provider of industrial Internet of Things (IoT) and edge hardware technology. Overview, founded by Tesla automation engineers, develops vision inspection platforms leveraging deep learning to automate and improve inspection processes.

The combination of Advantech hardware, specifically its new edge AI camera, ICAM-500, and deep learning technologies from Overview help manufacturers improve quality control, traceability, and speed for high-quality production line operations.

Automation is top of mind for manufacturers as quality control departments focus on yield, traceability, manual inspection costs, high turnover, and shrinking margin concerns. To help address these concerns, emphasis has shifted to improving and automating quality inspection processes. Overcoming these challenges was historically addressed with human visual inspections. Relying solely on personnel for visual inspection, however, is not only time consuming and costly, but also prone to human error.

A reliable, automated visual system can review product assembly at each stage of the manufacturing process, which simplifies and improves product inspection. Artificial intelligence and automation have eliminated the complexity of finding good and bad products, leading to zero defects in the manufacturing process.

The Snap Platform from Overview is an adaptable machine vision solution that handles everything from device management, algorithm development, product quality support, and traceability. When integrated with smart cameras, such as the Advantech ICAM-500, the Snap Platform automatically inspects from a PLC trigger, interval, or—in the case of video events—continuous capture.

“We are continually evolving our Snap Platform to provide new and existing customers with easy to use, powerful, inspection systems that also grow and scale with changing business and quality needs,” said Chris Van Dyke, CEO of Overview. “By partnering with best-in-class hardware providers for a reliable, end-to-end solution, we make device setup easier and faster. We are excited to bring Advantech into the fold and integrate our ‘Snap’ platform with its high quality, industrial edge AI devices.”

Unlike a typical vision system, the Snap Platform saves all relevant process data and creates a traceable visual record of every unit. Data is catalogued for easy search and analysis. This not only helps with traceability, but also allows for the discovery of yield loss sources. Users can determine the root cause of losses with data post-processing.

Embedded with NVIDIA® Jetson Nano™ modules, Advantech’s new ICAM-500 AI camera combines an industrial-grade image sensor, advanced LED lighting, and a variable focus lens with acquisition and AI computing capabilities. These features enable systems integrators and software vendors to integrate AI and machine vision into applications, while also efficiently performing AI automated optical inspection (AOI), AI optical character recognition (OCR), and object recognition at the edge.

“The ICAM-500 is a unique device, as the combination of NVIDIA computing modules and camera system offers image acquisition and AI inference functionality all within the same system,” said Carolyn Swan, Director of IoT Partnerships, Advantech IIoT Group. “Integrating the ICAM-500 with the Overview Snap platform creates a state-of-the-art solution for the manufacturing industry. Our built-in camera helps reduce latency challenges that usually occur due to the distance between IP cameras, the cloud, and AI inference systems. That low latency improves efficiency of on-site AI inference, creating an ideal solution for edge AI applications on the production line.”

Customers can deploy and manage the combined Advantech and Overview solution without the need of high-level technical expertise. Overview experts support the Snap Platform remotely, so customers do not need on-site machine learning experience. It also integrates with existing factory systems and communicates across networks to accomplish more efficient, lean, and profitable operations.

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