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Machine Vision Looks to 2017 as Transition Year

POSTED 01/19/2017  | By: Winn Hardin, Contributing Editor

Coming off of a tough year in 2016, machine vision insiders are looking to 2017 with high hopes — and a pinch of trepidation — as several key industries enter what many call transition phases. 

In the first three months of 2016, sales of machine vision systems and components fell 11% year-over-year. By Q3, sales had rebounded by 7%, reducing overall contraction to 3%. With projected overall sales of $2.3 billion in 2016, the market is expected to contract by 1% — still a 10% improvement over the start of the year.

Alex Shikany, AIA’s Director of Market Analysis, says the downturn in the first half of 2016 was mostly cyclical, influenced by tightening capex budgets, a soft global semiconductor market, and a slower manufacturing industry. 

Some suppliers, however, reported weak performance throughout the entire year. “We heard from many people that had a lot of variability month to month, and a lot of bad months,” says John Merva, Vice President, North America at Gardasoft LLC (Weare, New Hampshire). “That will bleed into the first-quarter, but we expect things will start to improve through the year. Everything happens slow in this market, but we will see growth in general.”

While 2017 is the “Year of the Rooster” according to the Chinese calendar, the machine vision industry might view it as the year of the transition. For example, semiconductor is transitioning from traditional processors and memory 18-month cycles to a new focus on embedded, low-power processing elements that could “flatten” some of the semiconductor industry’s wild cycles. Automotive is shifting to autonomous, while machine vision migrates from the plant floor to nonmanufacturing markets such as security and transportation.

Association Membership Climbs
By many accounts, the transitional nature of machine vision in the new year indicates a positive outlook. One sign of the industry’s optimism for 2017 is record-setting membership for the Association for Advancing Automation (A3), the umbrella group for AIA, Robotic Industries Association (RIA), and Motion Control & Motor Association (MCMA). More than 1,000 global automation companies are members of the three associations. As of December 31, AIA had 356 members. 

“It shows the value of trade associations during a period when more and more companies are looking to automate,” says Jeff Burnstein, President of A3. “The supplier community realizes they can connect with users and potential users by being part of the association, participating in key activities, and establishing their web presence at A3." 

A3 also has noticed big demand for its webinar series on how to successfully apply vision, robotics, or motion control. “Attendance has been great because of the need for education,” Burnstein says. “It’s the same thing for events. Conference attendance has been growing because many companies are just starting to automate.”

The New United States President: Good or Bad for Industry?
Even with a generally upbeat mood going into 2017, some vision companies say that with a new presidential administration in the U.S. comes questions about its impact on industry. “We don’t know what to expect, but one thing we know about the market is that extended uncertainty can create volatility/bearishness,” says Greg Hollows, Director of Machine Vision Solutions at Edmund Optics (Barrington, New Jersey). “You can see this going to into any presidential election.” 

“We need to wait three to six months to see what Donald Trump starts doing in office to determine if there’s certainty in one direction or another.” Hollows continues. 

“The U.S. could increase reshoring and boost manufacturing in general if the tax breaks promised by the Trump administration occur and leaves money in the pockets of businesses and will give us an uptick in the automation sector, including vision robotics” Merva says. 

IoT Readies for Primetime
A handful of applications and technological trends are expected to influence the vision industry in this coming year of transition. Ghislain Beaupré, Vice President of R&D and Operations at ‎Teledyne DALSA (Waterloo, Ontario) points to continued and increased focus on robotics, 3D imaging, and machine learning, along with growing emphasis on software to power artificial intelligence (AI) and artificial neural networks (ANN). Additionally, Beaupré foresees continued expansion of applications for non-visible imaging, including multispectral and thermal.

One trend that vision could capitalize on in 2017 and beyond is the Industrial Internet of Things (IIoT). “Machine vision is becoming more ubiquitous as the IIoT becomes more of a reality,” says Marc Marini, Director of Vision R&D at National Instruments (Austin, Texas). He cites the example of infrared cameras for asset monitoring.

With spending on the IIoT expected to reach $500 billion by 2020, enterprises have high expectations to boost productivity and revenues. “They want connectivity from the top down to all the machinery and controls so they can guarantee a product change and download the correct parameters to all individual components,” Merva says. “This interconnectivity will continue to proliferate, enabled by the GigE Vision and GenICam standards, which will continue to develop and become more useful to end users, integrators, and OEMs alike.”

Even with the promised gains of the IIoT, the market might not yet be ripe for picking. “The leading edge would likely happen on the production of these IoT devices,” says Wallace Latimer, Sales Director, Customized Optical Systems, at FISBA LLC (Tucson, Arizona). “The use of them in our space to update or change the industry is still to be determined.”

Buckle Up for Autonomous Vehicles
Demand for machine vision applications outside the factory is expected to climb as well in verticals such as intelligent transportation systems, surveillance, and autonomous vehicles. For self-driving cars, machine vision could offer distinctive solutions to an industry on the cusp of deployment.

“Deep learning or artificial intelligence (AI) platforms and penetration, as leveraged by great investment for autonomous driving, should continue to drive interest and expectation in solving challenges in the decision-making space of automation,” says FISBA’S Latimer.

Machine vision’s place in the autonomous vehicle market has yet to solidify, according to Edmund Optics’ Hollows. “These cars have had cameras for a long time, but very few machine vision companies sell into that market because of the commoditization of the product,” Hollows says. “And when you’re integrating things in the automotive industry, it’s difficult.”

He points to the cell phone market as an example. “Machine vision companies sell all kinds of things into inspection systems within the industry, but how many people are integrating components on device?” Hollows asks. “Is the autonomous vehicle market going to create a boom of new technologies that need to be inspected and machine vision grows? Do we have the resources and capability, or is it the adjacent industries like lift trucks, semis, and public transportation trains and buses where the volumes are lower and parts are integrated with higher margins?”

If the answer to these questions is “yes,” another question arises: Are vision OEMs and suppliers equipped for the task at hand? “2017 marks the beginning of the transition point because in five to six years we’re going to be seeing new players in the market and companies that will change radically,” Hollows says. 

The last time such a sea change occurred was between 2007 and 2009 when the recession hit. Says Hollows: “We went from expensive smart and regular cameras to low-cost GigE Vision cameras, and it changed the industry.”

Adapting to Customer Demand
Although opportunities in non-manufacturing market segments for vision and imaging are abundant, machine vision manufacturers confront several challenges. According to AIA’s Shikany, these industries “typically demand cameras with the ability to change focus and aperture while operating in differing ambient conditions.”

On the other hand, traditional manufacturing markets generally prefer camera systems with a fixed focus, distance, and lighting. By overcoming camera limitations, vision solution providers continue to penetrate non-manufacturing industries such as life sciences, agriculture, traffic, security, and surveillance.

Regardless of the markets they target, vision companies face another key challenge: satiating customers’ appetite for higher-bandwidth applications. Most often that requires cameras with increased resolution and speed. “Customers expect more functionality for a lower price,” says Shikany. “This mandate puts more pressure on vision manufacturers, distributors, and integrators to deliver feature-rich solutions at a modest cost.”

With a number of irons in the fire, the machine vision industry is poised for growth through the rest of the decade. “Between a healthy manufacturing sector and mounting interest in automation, North America will continue to be an appealing business environment for machine vision sales in the next three to five years,” Shikany says.

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