Most products manufactured in high volume with high accuracy at a low cost also can be made better and faster using machine vision. Although inspection at the end-of-the-line is great for final part checking, waiting for a remedy after a part has undergone numerous value-added stages in production often creates waste and rework. In addition, defects not caught at the source generate little information about the cause.
A Vision Area Network can be linked to plant and enterprise networks so any workstation with TCP/IP capability can display results, images, statistical data, and other information.
Previously, manufacturers would often multiplex vision cameras from a single processor in order to distribute vision sensing at multiple points on the production line. This tended to increase software complexity and integration costs to the point where the final system could not be easily scaled. But modern vision sensors, low-cost processing, and high-speed networking achieve infinite scalability. Vision sensors have one processor per camera, and because they can be linked together and managed as a system over a network, the overall costs and complexities of implementing distributed vision systems shrink dramatically.
Now manufacturers can reduce scrap, rework, and inventory problems by networking vision sensors throughout the production environment to catch defects at the source and possibly prevent errors altogether.
Ethernet is rapidly becoming a widely used network to provide higher-level computing systems access to plant-floor data. By linking enterprise level networks with production control and device networks, Ethernet lets intelligent control devices share information required for tasks such as automating production line changeovers and offers high-speed access to data generated by a broad range of plant floor devices for statistical process control.
Today’s highest performance vision sensors use advanced PatMax geometric pattern matching technology to reliably and accurately locate parts. This technique overcomes any problems encountered with variations in part orientation, size, and appearance.
Vision sensors generate an enormous amount of process information compared to most factory-floor devices. Consequently, vision systems have significantly influenced the use of Ethernet on the plant floor. Users needed to move large images and data files, so they turned to Ethernet because most firms had some in-house expertise with it at the corporate IT level.
Today, Ethernet is a key ingredient in the way people use vision on factory floors. Many vision sensors offer built-in Ethernet networking capabilities that let users link multiple vision sensors across the factory, integrate software for managing vision activity remotely, and share vision data with all levels of an organization.
A network of vision sensors provide a number of important benefits. First, it enables vision sensors to communicate with PCs, PLCs, robots, and other factory automation devices. Secondly, it allows data and images to be archived for trend analysis and continuous process improvement. Finally, networking lets vision sensors increase manufacturing agility by automating procedures such as changeovers for mixed-model processing.
Quality and process control
Although machine vision is well established in the semiconductor, electronic, automotive, and consumer products industries, the technology continues to expand into medical, pharmaceutical, and aerospace applications. Machine vision can be used for:
• Gauging: to measure the part or examine its critical dimensions.
• Inspection: to indicate if a part is good or bad based on its physical characteristics.
• Guidance: to accurately locate or place a part.
• Identification: to determine whether the correct part is present by inspecting its physical characteristics or reading a marked code.
Machine vision sensors typically are self-contained devices equipped to see and spot defects and other problems in manufactured parts or assemblies. Vision sensors look for manufacturing flaws using a combination of microprocessors and image analysis software to interpret video images and generate data about them. The vision sensors then report these data to other equipment, such as PLCs, robots, HMI/SCADA devices, printers, or other machines along the production line.
Vision hardware comprises a camera that captures an image of the item to be inspected, proper lighting to improve the contrast or features of interest, and optics, which accurately represent the image to the camera with minimal distortion and loss of resolution. This hardware works with a processor or vision engine to capture, digitize and display images for analysis, to guide a process, or to determine if a part is defective.
Vision software tools are the backbone of the vision engine. By comparing specific features of interest within the image to stored data that comprises a standard, these vision tools perform image processing and analysis of the captured image. A wide assortment of vision tools are available for performing many different types of inspection operations that let vision systems make decisions about a part’s quality, location, size, and identity.
Traditionally, vision sensors have been used to indicate when a product is good or bad, but with networking, more vision sensors are being used for control functions including quality control, process control, machine control, and robot control.
Networking vision sensors
To perform such control functions, vision sensors must communicate with other factory automation devices such as PLCs. The following industrial Ethernet protocols are most commonly used for this purpose.
• Ethernet/IP (Industrial Protocol) is a Rockwell-defined protocol that enables vision sensors to be linked to Allen-Bradley PLCs and other devices over a single Ethernet cable, eliminating the need for complex wiring schemes and costly network gateways.
• ModBus/TCP is an industrial network protocol defined by Schneider Electric and permits direct connectivity to Modicon PLCs and other devices over Ethernet.
• Profinet is an industrial communications protocol defined by Profibus International and allows vision sensors to communicate with Siemens PLCs and other factory automation devices.
All these communication’s protocols support vision area networks, which can be implemented in two primary ways. The first is linking two or more vision sensors over Ethernet to form a dedicated vision area network. In a vision area network, vision sensors can be managed by some type of host and they can exchange data, whether by a PC or another vision sensor. This type of configuration offers a number of key benefits. First, 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 complex cabling schemes to deal with. Vision data and images from all vision sensors can be collected ata central point and viewed on a single monitor. Failed images from each vision sensor are time and date stamped and can be archived for later review to determine the cause of specific failures.
The second way of implementing networked vision is to uplink a vision-area network to existing plant and enterprise networks. This provides a number of benefits. For example, it lets users manage vision activity from remote locations. 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.
By using vision at key process points, defects can be caught early and equipment problems can be identified more quickly.
In addition, up-linking to plant and enterprise networks lets manufacturers gain immediate access to the data related to the quality of their products directly from the vision sensors from any location 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.
The network for vision sensor management
Like a device-level network, a vision area network also can be easily up-linked to plant and enterprise networks, allowing any workstation with TCP/IP capability to display results, statistical data, and other information. For establishing a communication link between vision sensors and PCs at the enterprise level, the vision sensor should support a broad range of standard networking protocols, including:
• SMTP: (Simple Mail Transfer Protocol) capability, which enables e-notification of problems that occur on the production line. For example, if ten consecutive parts fail inspection, the sensor can send an e-mail to a computer, pager, or cell phone. This not only provides emergency notification that the line may need to be stopped, but also provides a second level of inspection monitoring in situations where operators may have missed an event.
• FTP: (File Transfer Protocol), which enables users to archive failed inspection images without writing customer software.
• DHCP: (Dynamic Host Configuration Protocol), where each vision sensor linked to the network is automatically assigned an IP address, enabling true plug-and-play performance. Sensors without this capability need to have an IP address manually assigned, which often involves asking an IT administrator for an available address.
• DNS: which allows users to name each vision sensor, such as “Transmission Line Sensor 1,” instead of relying upon on a 9-digit IP address. Without DNS, it may be a daunting task to keep track of all the vision sensors running on the line and often requires labels to be physically applied to each sensor with the IP address.
• TCP/IP: client/server, which enables vision sensors to initiate the transfer of results to other devices directly over Ethernet without developing any code.
• Telnet: is an Internet standard protocol, which enables remote login and connection from host devices.
Other emerging communication protocols are being used with vision sensors that provide powerful yet simple ways to integrate vision data, images, and graphics into factory automation systems. For example, ActiveX controls are useful for integrating vision sensor images and displaying graphics into third-party HMI and SCADA packages. In addition, today’s most advanced vision sensors support the use of industry-standard OPC communication tags to facilitate data exchange with other OPC systems and software such as controllers, distributed control systems, and distributed I/O networks.
Because vision sensors now can be distributed cost-effectively throughout the factory, manufacturers can make excellent use of their network for centrally maintaining and managing the ever-growing number of vision sensors running on their plant floors. Running 100 vision sensors across 12 production lines is one thing; setting up applications on each and then modifying them during product changeover is another.
That is why today’s most advanced vision sensors offer advanced software tools to centralize application development and network administration. Such tools make it extremely easy to add new vision sensors to an existing line, or copy existing vision sensor applications to new vision sensors for reuse on a new line.
This pen machine has excellent yield, but occasionally some parts are fed incorrectly or pen tips split during insertion. The vision inspection system quickly culls them out.
Switching from parallel I/O lines to serial communications provides similar benefits to machine vision as it does for production equipment: a smaller, lighter, more modular and scalable architecture that is easier to install, maintain, and troubleshoot. Networking lets manufacturers cost-effectively migrate machine vision from the end of the line to upstream production stations. By deploying vision sensors at key process points where there is significant value added, manufacturers can achieve tighter process control to error-proof production.
Finally, networking lets manufacturers centrally manage multiple vision sensors on the factory floor to improve data access at all levels of the enterprise.
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Filed Under: Factory automation, Mechatronics