A visual world
You know how important vision is in everyday life, so how in the world did users get along without it in their manufacturing processes? If you have not already gotten in on the vision act now that vision software and sensors are more commonplace, you might want to learn more about what is involved.
A February 2008 article by John Lewis, a chemical engineer at Cognex, and Nick Sheble, an InTech editor, covered the 10 most important questions to ask when selecting a vision sensor. (See complete article at www.isa.org/InTech/20080203).
Issues covered the importance of part location tools, which are software tools used to find parts within the vision camera’s field of view and usually the first step in any vision application—from the simplest robot pick-and-place operation to the most complex assembly verification task—and the one that usually determines whether or not the application succeeds or fails.
Built-in network communications also play a large role. They enable vision sensors to communicate pass/fail results data to PCs at the enterprise level. They also enable vision sensors to communicate directly with PLCs, robots, and other factory automation devices.
Users should also be aware of how easy it is to create custom operator interfaces and administer vision sensor networks. Vision applications do not usually require extensive runtime interfaces, but operators typically need to interact with the vision sensor in order to make modifications during part changeovers, change tolerance parameters, and determine the cause of part failures.
What about image preprocessing tools? They are a key factor in the overall performance of a vision sensor and should be a part of the standard offering. With such tools, the user can manipulate the raw image in order to highlight desired features or eliminate undesirable features.
In selecting character reading and verification capabilities, look for statistical font training capability, which allows you to create a single model or reference image from a series of images. This enables the sensor to better handle the range of normal variations in print quality it may encounter, whether it has to do with poor contrast, placement variations, degradations, or variations in stroke widths. Unless you can be positive every label prints with the exact quality seen in the model, the ability to develop a statistical model can be crucial to the success of your application.
To determine repeatability of a vision sensor’s gauging tools, present a part to the vision sensor and have it measure the part at least 25 times without changing part position, lighting, or any other variables. From this, you should be able to plot the repeatability of the measurements and make sure any variance in the results stays within the measurement tolerance.
As far as accessories are concerned, look for a vision sensor with its own family of compatible accessories. This places the burden on the vendor to test each accessory and confirm everything works together without any problems.
You should not need a PC, during configuration or in production mode. The sensor should offer true plug-and-play performance that enables you to quickly configure the application, from start to finish, right out of the box.
If you are looking for product support services, look for a vendor whose wide range of services start with the initial assessment of your application.
Another visual aspect in the automation world is the design automation software industry, which uses graphics, or visual data representations, such as 3D graphics models, charts, and control panels to replace complex tables filled with blurring numbers.
In his article, “The Advent of Visual Manufacturing,” David Prawel, president of Longview Advisors Inc., in Loveland, Col., said visuals lead to quicker understanding and faster response.
So much of product data is graphical, and more of that today is 3D, making the amount and type of information you can share richer than in 2D. For engineering, simulation, supply chain, maintenance and training, and sales and marketing, 3D models offer more product information and potential for immediate feedback and collaboration and faster decision-making.
Creating backend connections that automatically update maintenance manuals with 3D images as design updates take place keeps rework to a minimum. In this way, 3D also reduces errors and improves quality.
You can group together assemblies of parts by background computer programs into one or more associated work packages.
Product releases, sourcing, spare parts, service, marketing, maintenance, and every other downstream process can benefit from a visual manufacturing paradigm. Part catalogs become user friendly and intuitive, with simple search tools to find parts of interest, special packaging, or past purchase histories.
Ellen Fussell Policastro (email@example.com) writes and edits Automation Basics.
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