Page 21 - MetalForming July 2016
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into its press lines, and Heitbrink offers his take on controls evolution and its effect on automation, and where the metalforming industry likely takes that technology from here.
Big Data Supports Better-Informed Decisions
“From an operator’s standpoint, early controls used relays and minor communication devices to provide sta- tus and warning lights for operators. Then, smart digital displays with some analog meters added to the light and button display,” explains Heitbrink. “Today, computers in controls deliver much more, and in many cases a PLC does the work behind the scenes. So the screen is a PC, running an appli- cation that takes information from the processor and displays it in a nice, clean, user-friendly format. “
With the added muscle, more data can be fed into controls and processed for improved operator feedback, with this information then routed remotely in real-time, which enables monitoring and action away from the press line.
“Today, the buzzword with con- sumer-device controls is IoT, or Inter- net of Things,” Heitbrink says. “In our world, we refer to it as IIoT, or Industrial Internet of Things. In Industry 4.0, we get ‘cyber.’ We have a computer on every machine and now we have con- nectivity, which allows us to bring infor- mation to the cloud, or cyberspace, and then decide what to do with that information. A machine at the local operator level is very smart. We can get information to the cloud so that it
Press-line operators have a wealth of information at their fingertips, enabling quick shopfloor assessment of the stamping process. All of that data can be stored and ana- lyzed to deliver robust algo- rithms that can better predict machine or line performance, and recommend proper cours- es of action. It’s Industry 4.0 in practice.
can be processed. We then, for exam- ple, have the opportunity to perform some predictive analysis on why or when a machine will fail.”
Why is this such a tall order?
“In the metalforming industry, machines are built to last a long time,” explains Heitbrink. “To determine a likelihood of failure, processors can monitor certain data, perhaps vibra- tion, temperature, motor load, etc., and then log that data and examine it before and after a failure. But we need to experience failures to determine how an algorithm reads that data, and understand what exactly caused the failure and what must be addressed before the failure occurs.”
That’s difficult, Heitbrink offers, because unlike home appliances, which are in the field in very high vol- umes and tend to have shorter lives, industrial machines such as stamping presses and line equipment exist in smaller numbers and are longer-last- ing. So IoT enables plenty of consumer- appliance data to be captured. But automation and control providers, and stampers themselves, require a more- difficult-to-build database to produce reliable algorithms.
Improved Communication Eases Line Operation
A common communication path enables smart components in a press line to talk to each other and brings individual-machine and all-line data to a central location. This generates more information that can be analyzed and acted upon.
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