"Data acquisition is bringing the product engineer closer to the product," says Reynaldo Galang, principal engineer for AM General. This type of data acquisition gives engineers more "hands-on" involvement. Because of the instant feedback provided by portable data acquisition systems, a team of engineers can work together, exchange ideas and analyze each part of the problem, he says. Engineer Jeffrey Dowell, also from AM General, agrees. "We watch the test as it happens. It's like a doctor watching a heartbeat in surgery. The data is immediately available in the form we want, in a form we understand. It becomes much more of a living process. If we feel something, see something, smell something while the test is underway, we can alter the test methods at once." Traditionally, Dowell says, engineers had to wait days, even weeks, for results to come back after changing just one parameter on a project. There were many steps between the technician acquiring measurements and the actual presentation of results. Now, he says, feedback is instantaneous. "We can watch what is happening in real time and stop and say, 'Hey, what was that? Go back and rerun.' The time and cost savings are tremendous," Dowell asserts. Tom Desantis, president of IOtech, a data acquisition developer, adds, "It use to be that a measurement group had control of all the instruments that did the testing and the data would be handed back to the engineer. Nothing was done in real time. It took days, sometimes weeks for data to come back. Now engineers can be drawn in at the beginning. They can modify the test as it is performed, run another test. This drastically shortens turnaround time." The result, say observers, is that engineers can spend their time solving the problem rather than waiting for figures. "The form of developmental engineering is changing," Dowell notes. "With data acquisition, we become the test technicians as well as the engineers. We can look at the whole system in real time, while isolating various components." John Shotts, senior supervisor in the GM Research and Development's analytical chemistry and instrumentation department, sees data acquisition as a way to help lessen the work load. "In these days of downsizing, everyone has to do more," he says. "An engineer has to design the test, set up the test, and do the test. Modern hardware and software make this easy. A PC can collect the data, present the data, and analyze the data."
According to a study by the National Institute of Standards and Technology, one of the factors in the collapse of the original World Trade Center towers on Sept. 11, 2001, was the reduction in the yield strength of the steel reinforcement as a result of the high temperatures of the fire and the loss of thermal insulation.
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Robots are getting more agile and automation systems are becoming more complex. Yet the most impressive development in robotics and automation is increased intelligence. Machines in automation are increasingly able to analyze huge amounts of data. They are often able to see, speak, even imitate patterns of human thinking. Researchers at European Automation
call this deep learning.
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