Machine vision technology helps factory computers recognise objects with greater accuracy and reliability, and in many cases has replaced quality inspection performed by humans.
But that’s not the end of the story, because advanced automation technologies like machine vision can be further enhanced with the addition of machine learning, according to a report by technology market research firm ARC Advisory Group.
Machine vision systems provide object recognition capabilities and have demonstrated their cost effectiveness in inspection, measurement, scanning and object detection in manufacturing by improving consistency, productivity and overall quality.
However, an underlying limitation is that these systems are generally developed to handle a limited number of cases and they do not have the ability to train when an unexpected variation occurs, explained report author Anju Ajaykumar, analyst at ARC Advisory Group.
Machine learning can help solve that problem and is already being used to build greater adaptability into machine vision systems, enabling them to understand and respond appropriately to manufacturing variations.
This accelerates inspection processes and boosts productivity.
“Machine learning technologies and machine vision can be deployed profitably in a wide range of applications, allowing enhanced industrial automation and robust inspection processes,” Ajaykumar said. “As manufacturers make the transition to the smart connected factory and extend Industrial Internet of Things (IIoT) ecosystems across factories, plants and supply chains, efficient and flexible data analysis will be critical for operations of production systems and plant assets.”
She added: “End users are looking to do more with the data they collect from vision solutions. No longer is the data merely used for inspection or gauging and then discarded.”