Artificial intelligence (AI) is gaining favor as a solution for quality problems, but many manufacturers struggle with the perceived cost and complexity of implementing new technology.
Using continuous measurements reduces or even eliminates the production of faulty products and allows for consistent and repeatable production. This used to be an impossible task for small products.
Artemis Vision, a company with more than 10 years of experience in quality assurance for manufacturing processes, develops vision systems for industrial automated inspection and logistics optimization that deliver reproducible and reliable results.
For manufacturers navigating complexities of artificial intelligence (AI), one key challenge is balancing the advantages of new technology with immediate and long-term costs.
Strong price pressure combined with high quality requirements - the beverage and bottle industry faces the classic dilemma of many industries. This is also the case in the quality control department of a French manufacturer of plastic caps.
IDS is convinced that the changeover to sustainable action is the only right way forward and tries to develop resource-saving solutions together with business partners. After all, relatively "small" changes can make a big difference - for the environment and for the company.
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.
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