ASUS Keeps an AI on Quality Control in Smart Manufacturing

Automating quality control on production lines improves defect detection and ensures continuous operations. A customized automated optical defect detector leads one hardware vendor to build a software development kit to help system integrators improve their clients’ manufacturing processes.


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Image credit: ASUS 

The enormous growth in smart devices has increased demand for glass display panels used in the devices we see everywhere--in retail stores, restaurants, offices, and even built into vehicle dashboards. The continuing demand is driving growth in the flat panel display market. By 2026, the market is projected to reach $189.6 billion, with annual growth of more than 6 percent. That’s a lot of glass, and the potential for a lot of imperfect glass.

Anyone who has installed a screen protector on a phone can relate to the frustration of finding a tiny bubble that no amount of smoothing will eliminate. On a grander scale, glass manufacturers face that same concern every day. Now they are deploying artificial intelligence-based solutions to ensure their glass is free from imperfections.

The Looking Glass

Quality control in any manufacturing plant is critical, and manual inspections are common. That scenario isn’t ideal: it’s slow, costly, and unreliable. It’s also increasingly difficult as the speed of production outpaces a human’s ability to keep up with inspections.

Automating quality control processes eliminates the variability from manual inspections and streamlines operations, and ASUS is on the front of that trend. ASUS IoT worked with an industrial equipment system integrator to develop an IoT-based quality control solution for a client. The client needed a solution that could detect flaws on glass screens during the manufacture of smart phones. The solution would be integrated across the existing production line and had to operate with existing defect-finding equipment.

A Lean, Mean Inspection Machine

Working together, the SI and ASUS fitted the ASUS EBE-4U rackmount chassis with the Q170A-IM-A industrial motherboard, powered by Intel® Core™ processors. The result is a customized inspection machine that can be expanded as needed. Expansion cards can be added to the PCI and PCI Express slots, enabling the client to adapt or grow the machine’s capabilities as needed.

The custom machine operates with industrial-grade cameras with high frame rates to identify defects quickly and accurately. It uses artificial intelligence to identify and classify anomalies, and continued deep learning reduces false positives. Even when defects are discovered, the production line can continue to operate, which results in significant improvements in terms of cost, productivity, and efficiency.

Visual (Production) Lines

ASUS leaders expect manufacturing will see a rise in edge computing—particularly where visual inspection is required—and partnerships that result in co-developed AI solutions. ASUS is banking on the idea that AI and machine learning will continue to automate processes in manufacturing and production across multiple industries.

With the success of the automated visual inspection machine, ASUS recently introduced AISVision, an AI toolkit and software development kit that allows developers to build computer vision capabilities using ASUS techniques. AISVision has three modes: Trainer, Runtime, and Scheduler, for AI training, inference, and batch training. It is designed to support integrators that want to build or augment automated optical inspection systems, and it includes models for object detection, object classification, segmentation, and anomaly detection.

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