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Steep growth in machine vision, industrial scanning

VDC predicts these vision-based technologies will expand as more companies shift to “factory of the future” strategies
Tuesday, August 6, 2019 - 07:00
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Machine vision and industrial barcode scanning solutions are experiencing rapid growth as more companies leverage the technologies to implement “factory of the future” strategies and to enhance supply chain and logistics operations. A new report from VDC Research, “Machine Vision Solutions and Industrial Barcode Scanners,” predicts that machine vision solutions will grow from just over $6 billion in global shipments in 2017 to roughly $10 billion in 2023. Industrial barcode scanning, meanwhile, will expand from roughly half a billion in shipments to nearly $800 million in the same period.

According to VDC, machine vision technology can help enable vison-guided robotics in packaging, warehousing, parcel handling and other applications, and the use of deep learning and artificial intelligence can further improve system performance by enabling the systems to do a better job at recognizing attributes. “Machine vision systems are increasingly being integrated throughout the entire production line, rather than only at the end to inspect the finished good,” said Andy Adelson, AutoID and Data Capture Analyst at VDC. 

Barcode scanners, meanwhile, are growing more sophisticated while costs are dropping and performance is improving. Imaging–based scanners now account for nearly 75 percent of global scanner revenues.

According to Adelson, this shift toward imaging scanners has been driven in part by the amount of data that needs to be captured and used. “The data requirements are much greater than what was originally enabled by a laser system,” Adelson says. “Image-based scanning provides a much higher density, and therefore captures more data. It’s no longer a matter of capturing a product name and price; you are capturing a full supply chain record from the raw material to the shelf. You are verifying the authenticity of the product and other information. These applications require higher density barcodes.”

That data density has led more users to implement two-dimensional (2D) barcodes, which cannot be read with laser scanners. In addition, image-based systems can scan multiple barcodes from the same label simultaneously.

Advanced applications drive growth
Adelson says that machine vision and scanning will play a key role in factory of the future applications, although exactly when those applications will truly arrive remains in flux. “We still see those applications happening at the tail end of a five-year forecast before they become pervasive, he says.

In these advanced manufacturing and supply chain applications, data collected in real-time throughout the production or shipping process can be used to drive more automated functions – for example, flaws identified by machine vision could trigger an automatic machine recalibration, or scans of outgoing goods could initiate re-ordering without human intervention.

Machine vision is being deployed across a variety of applications both in manufacturing and logistics. Adelson cited inspection applications in the flat panel display and solar panel industries, where the systems have advanced to the point hat they can evaluate single pixels in a display or segments of an optical panel.  

In the supply chain, vision systems can help ensure that cases or pallets meet size and weight requirements or inspect packages for damage, as well as enable more complex solutions. “The next level is a provider like Amazon that has to look at boxes coming down a line that are different sizes and shapes,” Adelson says. “There is more variability, and you don’t always get a predictable parcel or a barcode scan. There’s a higher degree of complexity.”

Both the pharmaceutical and printed circuit board industries have embraced vision and imaging based scanning to help improve traceability of variably sized products, as well as for quality control and authentication. 

These solutions can also aid in streamlining recalls, a function that could prove useful in automotive applications, where recall activity has increased substantially over the past decade. “You can identify which products are at risk and have retailers or consumers only get rid of those specific batches,” Adelson says. “Machine vision really has a compelling value proposition there.”

 

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