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Advances In Networking for Machine Vision
by Evan Lubofsky - Cognex Corporation Posted 03/28/2002
While many manufacturing processes could benefit from automated inspection at several key process points, the traditionally high price of machine vision systems has often proved a deterrent to using vision at any stage other than the end of the line. End-of-the-line inspection systems can do a great job at final part checking, but waiting until after a part has undergone numerous value-adding stages of production can often mean costly and time-consuming rework of a bad part. And, since defects are not caught at the point of occurrence, little information can be generated about why defects are occurring in the first place.
Manufacturers could, however, expand an end-of-the-line system to other points on the production line by multiplexing vision cameras from a single processor. The benefit here was that the hardware cost associated with each inspection point was minimal. The downside was that, linking from a single processor, vision processing had to be divided up among multiple cameras, resulting in reduced vision performance at each point. And then there was the issue of scalability, which in technological terms can be defined as how well a solution to some problem will work when the size of the problem increases. With a multiplexed camera configuration, scalability is inherently poor since only a finite number of cameras can be used no matter how many additional uses a manufacturer might find for vision.
Finally, there was a great deal of software complexity and integration costs involved in managing and maintaining multiplexed cameras. Special programming was typically required to synchronize camera triggers and outputs, and a problem with one camera often meant the entire system had to be taken offline.
Distributed vision takes on a new look
Recent advances in machine vision sensor technology have enabled manufacturers to distribute vision throughout the manufacturing process without the limitations associated with a multiplexed camera approach. Because of the compact, affordable nature of many vision sensors available today and improvements in processor technology, it has become feasible to have one processor per camera, resulting in maximum vision performance at every point on the production line where a sensor is placed, and greater assurance of uptime. And, because each sensor is an independent device, the complexity associated with synchronizing multiple cameras off of one processor is eliminated.
Perhaps more importantly, it is now cost-justifiable for many manufacturers to add vision in enough places so defects are caught at the source. Consider a bottling supplier, for example. In the past, the company may have only used a vision system at the end of the line to ensure labels are present and not skewed. Now, the same manufacturer can justify the addition of a dedicated vision sensor further downstream at the labeler station to inspect the bottles the moment labels are applied. This way, if a label is misapplied, or not applied at all, operators can stop the line before a whole batch of defective bottles is produced. Then, based on the nature of the defect found, the labeling equipment can be adjusted accordingly.
Eventually, the bottling supplier may want to add automated inspection at other stages on the line, such as filling, capping/sealing, and inserting. With a multiplexed camera approach, there are only so many vision cameras one could use without having to absorb the cost of another vision system. With vision sensors, having one camera per processor means having the scalability to add vision to these points, and others in the future.
Rather than having a vision system at the end of the line only, companies are linking multiple vision sensors together into a Vision Area Network, enabling automatic inspection at each process point. This enables defects to be caught before additional value is added to products.
Ethernet: The missing link
Because machine vision can now distributed very cost-effectively throughout the manufacturing processes, vision is finding its way into more and more places throughout the factory. As a result, many manufacturers now need a centralized way to maintain and manage the ever-growing number of vision sensors running on the floor. Running 60 vision sensors across 10 production lines is one thing; setting up applications on each, and then modifying them during product changeover, is another.
Over the past decade, Ethernet networking has become a more integral part of the manufacturing process, transcending down from corporate IS level networks to the plant floor. Replacing what have traditionally been costly, complex proprietary network connections, Ethernet provides higher-level computing systems access to the plant floor, allows intelligent, high-speed control devices to share information required for tasks such as work-cell coordination, and offers high speed access to plant floor data from a broad range of plant floor devices.
Now, Ethernet is becoming a key ingredient in the way people use vision on the factory floor. Today's most advanced vision sensors offer built-in Ethernet networking capabilities that enable users to link multiple vision sensors across the factory, manage vision activity remotely, and share vision results data with all levels of the organization.
Consider the bottling line example mentioned earlier, where vision may need to be implemented at four separate points on the line: filling, capping, labeling, and inserting. To enable data exchange between four conventional vision systems on this line, one would need to establish a serial communications link by linking several serial cables between each system. Then, to view inspection results, one would either need to have a separate VGA monitor at each inspection point to view inspection results, or have the results sent over serial lines into a single workstation, where an HMI package would be required to consolidate and present the results. In contrast, a network of vision sensors linked over Ethernet enables direct peer-to-peer communications between each sensor over a single line, so there are no complicated cabling schemes to deal with. And, because the network of sensors is managed by a host, vision results data from all four sensors can be collected at a central point, and viewed on a single VGA monitor. The host may also be used, for example, to archive failed images from all four vision sensors which are often use to better determine why certain parts failed.
The second way of implementing networked vision is to uplink a vision area network to existing plant and enterprise networks. This can provide a number of benefits. First, it enables users to manage vision activity from remote locations. For example, one could set up and modify vision applications, share applications with other plant sites, and remotely troubleshoot problems with technicians, all without ever leaving the office. Additionally, uplinking to plant and enterprise networks enables manufacturers to gain direct access to the data related to the quality of their products directly from the vision sensors from anywhere in the plant, the enterprise, or anywhere within their global organizations. Quality engineers may want to view SPC data, while management may want to keep an eye on production output. All it takes is a workstation with TCP/IP capability.
Instead of being reserved for end-of-the-line part checking, machine vision can now be cost-effectively deployed at various key process points along the way, and centrally managed over Ethernet. By distributing vision at more points in the process, manufactures can respond more quickly to equipment problems and achieve better process control. And, with Ethernet connectivity, the ability to centrally manage multiple vision sensors running on the floor, and make vision results data more accessible to all levels of the enterprise, is greatly improved.
When evaluating vision sensors, it is important to find out which network and fieldbus protocols the vision sensor supports. For establishing a communication link between vision sensors and PCs at the enterprise level, make sure there is support for the following protocols:
For connecting vision sensors to factory automation devices such as PLCs
and robots, look for support for the following: