Track-and-Trace Offers Big Opportunities for Machine Vision

Customization, quality, and automation are driving companies to adopt track-and-trace data-collection systems across all industries. Manufacturers and product designers are creating ever-increasing numbers of customized products, leading to increased expectations for flexibility in production lines. At the same time, to fully realize the benefits of automation, a plant needs centralized control and accountability to keep key management, engineering, and maintenance staff aware of status changes in real time. Furthermore, quality standards are rising around the world.

Put these three industry drivers together, and you can see why product tracking is “taking off” throughout industrial environments, according to Christoph Wimmer, Global Business Development Manager with Microscan (Renton, Washington). “Customers see the advantage of adding traceability to optimize production and to better see where they have bottlenecks and how they can get rid of them,” he says.

As a provider of systems for product identification and traceability, Wimmer says Microscan is already keenly aware of the growing demand into new market sectors. “We expect to play a much greater role in all of manufacturing,” he adds.

Ever Wanted to Be a Know-It-All?
The battle of technologies for track-and-trace is not just about laser- versus camera-based code readers, says Mark Kremer, Vice President, Machine Vision & Laser Marking at Datalogic Industrial Automation (Bloomington, Minnesota). “We think track-and-trace is one of the biggest market applications for machine vision today,” says Kremer.

With machine vision for object location, laser- and print-and-apply marking systems for code application, code-reading for verification and track-and-trace, and middleware software partners to connect it all together using image-processing and data-handling software applications, Datalogic is positioning itself to have the ability to bring “any application, no matter how small or how large, to successful completion,” Kremer notes.

Critical, too, is the need for track-and-trace equipment to be user-friendly and easy to set up. Kristian Bartell, ‎Product Marketing Manager for Leuze Electronic (Owen, Germany), says the company is launching in early May its DCR200i image-based scanner. Priced affordably for a wide market penetration, the scanner offers 1D and 2D compatibility, four configurable I/O points, plus Ethernet connectivity. “You could connect a computer to the scanner and set up the device in two minutes without downloading software,” Bartell says. VPN connectivity allows for connections to the device from anywhere, making distance monitoring relatively easy.

The DCR200i is one example of how manufacturers are meeting demand for user-friendly interfaces. “There’s a shift to one-button and two-button setup with no software downloads required to get a scanner up and running,” Bartell says.

In assessing laser- versus image-based scanning, the long-term trend is toward image-based systems, says Wimmer. This trend sets the stage well for machine vision to take its place among track-and-trace solutions.  Even so, some laser scanners are less expensive than image-based systems. For example, an image-based system for long-distance code-reading tasks may cost up to twice as much as a laser scanner. Wimmer says that price point may be justified for a reader that includes a lot of optics to handle complex reading tasks.

However, medical-device imaging still uses 1D codes in the majority, and laser scanners “have an advantage there,” he says. For one thing, laser scanners typically offer the easiest setup because of the relatively minor complexity of 1D code-reading applications. For another, their space requirements can be smaller than for a camera-based scanner due to the size and number of internal components. Smaller footprints can offer a “huge advantage for customers who have less space for a reader.”

What’s more, many medical laboratories continue to use handheld laser scanners. “Moving to a 2D code would mean having to upgrade the whole lab,” Wimmer says. “A lot of labs are trying to avoid this, so for backward-compatibility purposes, they’re sticking with 1D codes. A hybrid approach that is gaining popularity is to use 1D code as the main data set and include 2D code as a sort of add-on with additional information.”

For consumer electronics, Wimmer says that a 1D code is usually printed on a label affixed to a printed circuit board (PCB) panel, while 2D codes are often marked on the PCB itself due to space considerations. Manufacturers who employ 2D marks must be equipped with image-based systems to read their codes. Asian manufacturers tend to use 1D codes on PCB panels and therefore typically use laser-based technology, while U.S. manufacturers utilize image-based technology since they will more commonly include 2D codes on panels to ensure cradle-to-grave traceability.

Range of Products
Bartell says that the bread-and-butter offering for Leuze Electronic is its BCL300i series of fixed line scanners. These offer embedded connectivity and dual port switches that can be daisy-chained. Its big brother, the BCL500i, offers longer read ranges, while the 600i line offers the same internal components as the 500i but includes a blue laser scanner rather than red — a bit of a unique offering in the industry. “The blue laser covers both the short and the long range without the need for multiple scanners and adjustable focus,” he says.

In addition to laser scanners, Leuze offers image-based scanners for industrial use: the LSIS400i series, which offers 1D code reading and measurement tools for tracking and measuring, and the DCR200i which offers three different optics to choose from in the range of 40 mm to 360 mm. Bartell says that while the system still requires some form of supervisory software to collect and manage the data, the readers are web-configurable with everything embedded in the unit itself and come with discrete I/O to simplify industrial networkability. The packaging industry is a primary market focus for Leuze, followed closely by pharmaceuticals. These industry sectors tend to have more robust standards and regulatory guidelines than other sectors, supporting demand for track-and-trace technology. “Other industries are not quite as regulated,” he says.

Automation as a Driver
The move to adopt more product-tracking technology is supported by increasing automation, which, in turn, is driven by rising labor costs, says Microscan’s Wimmer. “Automation is becoming the norm everywhere, even in China,” which traditionally has been a source of low-cost labor. He notes that electronics manufacturer Foxconn has added robots to its production lines in China to control labor costs. The manufacturer’s expanded use of automation brings with it an increased need for product tracking.

Rising quality standards on the production line also drive track-and-trace deployment, which is leading to some hybrid applications, according to Wimmer. For example, some manufacturers have fully automated production lines, while others have a blend of automated lines and manual work cells.

“I see a lot of combinations,” Wimmer says. “All of these require quite a bit of traceability.”

Track-and-trace applications are one of the high-volume drivers molding the machine vision industry today. Yesterday’s smart camera, at a fraction of the size, has become today’s flexible machine code reader, bringing more intelligent capability to what has traditionally been a “dumb” application. As more industries, through risk management or regulation, turn to track-and-trace to limit liability and improve quality, machine vision will continue to support and benefit from these moves.