Navin Dedhia has been a pillar of the quality community since the 1960s, speaking and working on five different continents about the importance of quality.
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.
Even with the availability of hundreds of standard precision tools and gages, sometimes measuring challenges are best solved with a specially made gage. It is critical to work hand-in-hand with engineers who are dedicated to making sure that an accurate and easy-to-use custom-made solution can be attained for specific application requirements.
Quality standards require that measuring equipment be calibrated prior to being put into service. In addition, the maintenance of measuring equipment requires recalibrations at regular intervals.
In the middle of the most chaotic, uncertain months of 2020, manufacturers discovered that the perfect antidote was to double down on quality and reliable delivery—turning to their enterprise resource planning (ERP) systems for the timely insights needed to navigate rapid changes in market demand and resources across their supply chains.
With the manufacturing industry growing more complex every day, it’s hard to imagine operating a manufacturing enterprise without an ERP system. The software provides a critical central communication point for the business, handling all activities from quote to cash and everything in between.
“There is no reason and no way that a human mind can keep up with an artificial intelligence machine by 2035,” predicted the techno-futurist philosopher Gray Scott. But the truth is more nuanced: automation will create as many opportunities for humans as it reduces. Here’s how manufacturers can greatly enhance their processes—and address the U.S.’s skills shortage.
With the introduction of augmented reality into assembly and inspection processes, cutting-edge industry 4.0 research is uncovering best practices to maximize quality.
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.