Today, most machine vision systems are limited to performing simple quality checks or detecting the presence of components. They act after the fact — raising alarms once a defect has occurred. Adjustments to production settings are then done manually by operators, often too late to prevent waste or inefficiency. These systems are sensitive to change and cannot adapt dynamically when process conditions vary.
Computer Vision changes this reactive approach, with its feature Smart Supervisory Machine Vision. The latter, serves as a link between production process supervisory control and machine vision. Furthermore, it integrates machine learning, sensor- and process data and advanced process control.
Transform your machine vision system with Orise‘s Computer Vision, turning it from a basic quality monitor into an intelligent, proactive optimization tool.
Standard machine vision applications typically inspect for quality or presence and trigger alarms or actuator responses when issues arise. However, process adjustments are often done manually and offline, leading to extended periods of sub-optimal quality. Issues are usually flagged only after they exceed the thresholds set in the computer system.
Thanks to our expertise in computer vision, machine learning, and industrial Advanced Process Control, we go beyond traditional applications. By deriving process parameters from industrial camera images and integrating other sensor and process data, our predictive models and AI algorithms detect anomalies and process drift in realtime. Our smart software then proactively adjusts process parameters before issues arise.
The approach enables automated, real-time tuning of process parameters—supervisory control—to optimize product quality and minimize defects.
The result is a transformative approach to machine vision that not only enhances product quality but also boosts operational efficiency and productivity, while significantly reducing downtime.
Curious about what we can do for you?
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