Industrial automation has seen phenomenal growth over the last century. The advancement in science and technology has made manufacturing on a large scale possible. The onset of Industry 4.0 also has many organizations embracing new industrial practices that digitize their production processes. Hermary has always been at the forefront of machine vision technologies. For over 30 years, alongside our integration partners, we have created game-changing systems for many industries.
Machine Vision for Industry Professionals
More often than not, though, we find ourselves humbled by our partners’ sheer ingenuity in incorporating machine vision into their solutions. By sitting down with Hermary’s Applications Engineer, Josh Harrington, we hope to create an evergreen learning environment for all industry professionals to share knowledge about machine vision.
In this video, we will start by checking off some of the most frequently asked questions:
- What is machine vision’s purpose?
- How is it useful in industrial applications?
- Major types of machine vision.
In future episodes, we will cover more technical aspects of machine vision: hardware technologies used to develop 2D and 3D solutions, how to develop machine vision solutions for different applications, how to manipulate the data and more.
Machine vision works best when working alongside human operators. If you would like us to cover any specific subjects or have any questions or feedback, leave us a comment below or contact us.
Hi, welcome to machine vision for industry professionals an education video series to help engineers learn about machine vision and how to work with it.
In this video, I will introduce what machine vision’s purpose is and how it is useful in industrial applications. We will then break down and discuss the two major classes of machine vision devices: 2D and 3D. By the end of this video, you should have a basic understanding of the role machine vision can play in automating or improving industrial processes as well as technologies used.
My name is Josh Harrington, and I am a product applications engineer here at Hermary, a leading manufacturer of machine vision hardware. I am here to answer common questions regarding machine vision and share my experience in the machine vision field.
What is Machine Vision?
A common misconception is that machine vision is simply attaching a camera to a machine and getting back photos or videos of what that machine sees. While in certain applications this may be desirable, machine vision can be generalized more broadly.
Here at Hermary, we define machine vision as the digitization of the physical world in order to make a decision on how to inspect or interact with a process or task. This typically will involve hardware, to gather information and software to process this information. This is analogous to the way our eyes capture light from the world and our brain determines what we are looking at.
Machine vision hardware can broadly be split into two primary categories: 2D and 3D. 2D devices capture two-dimensional information typically in the form of light intensity and 3D devices capture 3D information most often relating to the physical structure of whatever is being viewed.
2D Machine Vision
2D machine vision devices are by far the most common form of machine vision and is the most easily relatable to as it is the same type of perception that we as humans have with our eyes. 2D machine vision relies on gathering light and identifying features by changes in contrast. There are a wide range of lighting techniques, camera configurations, and types to gather information on a huge range of applications. Examples of just a few applications are barcode scanning, print inspection, mail sorting, PCB verification, and many many more. A major way that 2D machine vision has been evolving recently is to include both the hardware and software to perform many of these tasks all within a single device. These types of devices are often referred to as smart cameras.
3D Machine Vision
We often say don’t try to solve a three-dimensional problem with a 2D solution and while 2D machine vision is suitable for many tasks, it can fall short when trying to address applications that need accurate, reliable information regarding the 3D nature of a scene such as the shape, position, dimensions or orientation of an object.
3D machine vision has had phenomenal growth over the years and is becoming more and more commonplace in industrial applications and continues to grow as 3D machine vision devices become more accessible and the ability to process 3D data becomes easier.
3D machine devices have proven themselves in applications involving: quality control, inspection, machine guidance, object positioning, dimensional monitoring, and physical feature identification.
Machine vision’s ability to reliably automate respective tasks, be used in potentially hazardous environments, and fill the gaps in shrinking labor markets has driven machine visions to recent exponential growth. Machine vision is integral to automation and will continue to grow as it is applied to more applications across all industries.
In the next video in this series, we will do a deeper dive into 3D machine vision, the devices, and the data. If you have any questions drop a line in the comment section below. Thanks, it’s been great to have you here.
Thanks for your blog, nice to read. Do not stop.
Im obliged for the blog post.Really thank you! Want more.
I couldn’t resist commenting. Well written!
A good introductory to machine vision and machine vision applications and also the comparison of 2D vs. 3D solutions for various use cases. I am looking forward to the future episodes.
Thank you for making these educational videos. I look forward to seeing more in the future.
Thank you, Sally. Stay tuned for more episodes!