QUALITY CONTROL 
MACHINE VISION

The Optinence machine vision system acquires images of your product, and then uses advanced artificial intelligence to process, analyze and measure various characteristics of the product. This is ideal for error-proofing applications.

Our sensors can inspect multiple areas of interest within a single image, as well as perform multiple inspections relying on different tools.

Our Benefits:

Accuracy

Machines have clear advantages in precision over the human eye.


Repeatability

Machines can conduct an inspection task over and over again in the exact same way without fatigue.


Speed

Machines can inspect parts faster. Particularly when inspection takes place at high speed, such as on a production line, machines offer an advantage in productivity and efficiency.


Cost

Because machines are faster than humans, an automated inspector is worth several human inspectors.

Video Camera Lens

QUALITY CONTROL 
DEEP LEARNING

In most factories quality inspectors inspect product quality after the product is manufactured. A manual effort with rejected products resulting in wasted upstream factory capacity, consumables, labor and cost.

With deep learning you can solve complex and challenging inspection goals that were, in the past, not possible with traditional rule-based machine vision systems.

Key capabilities of Exora Optinence

Classification

Classify products into various categories - including Pass or Fail.

Transcription

Read data from images and convert them into a format that makes it suitable for your task.

Analysis

Analyses images to mark out regions of interest such as scratches or cracks.



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OPTINENCE ASSET MONITORING

Advanced Solutions

Smart solutions are at the core of all that we do at Exora Labs. Our main goal is finding smart ways of using technology that will help build a better tomorrow for everyone, everywhere. Click below to learn more about the technology behind our Technology Company, or get in touch to set up a meeting with one of our representatives.

Cogs in the Machine

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