Plastic injection moulding is a difficult application for machine vision. The highly reflective surface of plastics is hard to illuminate, and the fact that the same production line can create items of different colours and shapes is problematic for traditional solutions.
Packaging and labels contain key information on food products and drugs. A minor mistake on either could have serious repercussions that impact a product's safety, regulatory compliance and consumers' satisfaction.
Camera Specs - Not the Frontier in the Era of AI - Autonomous Machine Vision (AMV) Offers a New Approach to Visual QA
Machine vision engineers are pushing the frontiers of camera specifications to offer solutions with incredible resolution. Yonatan Hyatt explains why Autonomous Machine Vision (AMV) is pushing the boundaries of artificial intelligence, not camera specifications.
In the vision market, we're really at that initial AI and machine learning phase. AI for inspection excels at locating, identifying, and classifying objects and segmenting scenes and defects, with less sensitivity to image variability or distortion.
Manufacturers are facing a number of challenges, but perhaps the biggest of them all is the implementation of automated material handling solutions. SICK, Inc. has the answer to this problem with a system-solution approach.
There are many factors to consider when deciding on a vision system in your automation system. Three of the biggest are hardware, lighting, and lenses.
Instrumental is attacking the 20 to 35 cents of every $1 spent in manufacturing that is wasted. That waste comes from literal scrap at the various factories in the process, returns, mistakes, extra experimentation, travel, and engineering time that wasn't used efficiently..
The productivity benefits of Autonomous Machine Vision
Manufacturers can now finally benefit from powerful visual QA systems with no downtime, very short implementation lead times, rapid diagnostics and far less testing, training and spare parts.
Handheld barcode scanners are essential whenever specific products, clinical samples or work-in-progress (WIP) parts need to be reliably tracked without the luxury of a fully automated system.
Depending on how long a part or product needs to remain traceable, the relative permanence of various marking methods could be a game-changer. In the aerospace industry, for instance, parts could be in use for as long as 30 years.
As the plant floor has become more digitally connected, the relationship between robots and machine vision has merged into a single, seamless platform, setting the stage for a new generation of more responsive vision-driven robotic systems.
"The startups that have made it to the final competition are indicative of the levels of innovation in the machine vision and imaging industries," according to Jeff Burnstein, President, AIA. "I don't envy the job in front of our judges having to select only one winner."
White Paper - An Introduction To Machine Vision Toolkit
An efficient manufacturer must get products in and out of a cell quickly and reliably. Vision systems paired with robotic operations can put an operation at a competitive advantage by providing opportunities to make more and streamline the process
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Pleora's AI Gateway is the most straightforward way to train and deploy artificial intelligence (AI) algorithms for inspection applications. With "no code" training, plug-in AI skills for detection, sorting, and classification, and processing flexibility to support open source and custom algorithms, designers and users can immediately reduce costly inspection errors while preparing for advanced Industry 4.0 and IoT applications.