“Garbage in, garbage out” serves as a simple reminder that successful machine vision systems must start with quality data. Current challenges require flexible machine vision systems and models that can keep up with the speed of technology.
There is no question that the COVID-19 pandemic dramatically impacted business practices across industry segments worldwide. Manufacturing was no exception and 2021 will be the year of reinvention through an emphasis on transforming business models.
CoaXPress (CXP) has developed into a new standard in industrial image processing in recent years. The CXP interface, which is particularly relevant whenever high data rates and short latency periods are called for, is now available in a new version with more improvements.
A Growing Number of Manufacturers are Using Deep Learning Tools, a Subset of Artificial Intelligence, to Reduce Waste and Improve production. But, Experts Say, Some of it is Just Hype.
An increasing number of manufacturers are turning to deep learning, a subset of artificial intelligence (AI), to assist in image analysis processing, experts say.
Over the last couple of decades, stemming from changes in demand, competition, and market pressures, manufacturing has become a more complex and fraught affair requiring increased flexibility with a narrower margin of error. We can sum up this changing environment in three long-term trends affecting how stuff is designed and made: mass customization, increasing SKU proliferation, and shorter product cycles.
Manufacturing industries have been striving for years for a robust quality control solution which can reliably sort out bad parts of the dispensing process without causing much production downtime. What the industry craves is a robust 3D solution that provides a 360° view of the bead regardless of the dispensing direction.
It is impossible to overestimate the critical nature of keen and constant visual inspection in any production process. That’s why an advanced vision system is vital for any of today’s advanced production lines – as well as for “yesterday’s” older and more issue-prone lines.
Vision guided robotics (VGR) is an automation technology well-recognized for enabling greater flexibility and higher productivity in a diverse set of manufacturing tasks over a wide range of industries.
Part 1 of this three-part series examined how to identify characteristics of the object and the background you can use to create contrast with the illumination source for your machine vision application. This second part looks at how you go about choosing a light source to take advantage of the characteristics that create contrast.
Imaging lenses enable machine vision systems to inspect, sort, and measure objects for a variety of applications including manufacturing, robotics, autonomous (self-driving) vehicles, and more.