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Manufacturing Technology Insights | Monday, January 06, 2020
The growing use of machine vision is offering many benefits to manufacturers including increased quality, productivity and flexibility.
FREMONT, CA: Machine vision is becoming a game-changer in the manufacturing by helping manufacturers in improving the production quality, predicting production flaws in manufacturing lines, and cutting down costs. Here are some of the use cases of machine vision in manufacturing.
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Predictive Maintenance
Predictive Maintenance is the process of using machine learning and IoT devices to monitor data on machinery and components, often using sensors, to collect data points and identify signals or take corrective actions before assets or components break down. In the process of predictive maintenance, machine learning and IoT devices are used to analyze data on machinery in the manufacturing floor. It often uses sensors to collect data and identify signals or take corrective actions before assets or components break down. In such cases, machine vision will play a role by doing predictive maintenance.
The role of a barcode scanner is significant in the manufacturing industry. There are several benefits barcode scanners provide for manufacturers like reduced time and cost, minimized errors and decreased stress levels. Manufacturers can automate the overall scanning process by powering machine vision systems with advanced Optical Barcode Recognition (OBR), Optical Character Recognition (OCR), capabilities and other image processing technologies.
Inspecting goods
Quality control and product inspection are two main activities of the industry that cannot be ignored. Manufacturers can detect flaws, or cracks, in a physical product, with machine vision systems.
These systems can also check accurate and precise measurements of components which sometimes not done accurately with human eyes. All these issues can be eliminated easily with the machine vision system and it will also optimize and streamline these processes in much lesser time.
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