Industrial machine vision cameras and sensors are finding their way into applications both on and off the manufacturing floor.

When an engineer begins the process of specifying a new machine vision system, they will often think very carefully about the line speed, the optics, and the image processing software.

You’ve learned about light sources, lenses, cameras, camera interfaces, and image processing software. Now, you may be wondering exactly how to design and implement a complete, successful machine vision system. 

Over the past decade manufacturers have increasingly turned to flexible, customizable automation platforms to meet the demands of high mix/low volume orders and ensure their long-term survival in a competitive manufacturing environment.

In the world of machine vision, as in any tech field, there is a distinct divide between hardware and software. The hardware includes components of machine imaging systems such as the physical camera, lensing, cable interfaces, the PC or processor, etc. and are defined by rigid specifications (i.e. resolution of a camera, processing power, bandwidth of interface). 

Artificial intelligence (AI) is one of the most hyped technologies of recent years, and while it promises new cost and process benefits for inspection applications, deployment remains a challenge.

Frame grabbers are essential components in machine vision systems that provide ultra high-speed, high-data image capture from one camera or multiple cameras simultaneously. 

Originally made popular by the introduction of Rethink Robotics’ Baxter, so-called collaborative robots have created a lot of excitement around the industry over the last few years.