Using PACs and PLCs for Data Acquisition, Logging & Analytics

General-purpose machine controllers, whether they are PACs, PLCs, or PC-based controls, are offering more support for data acquisition, data logging, and analysis than ever before. But the key will be how systems engineers use these more expansive data sets to improve machine performance.

"PLCs and PACs are becoming more powerful by offering more memory and more processing power," Jeff Payne, product manager for PLC, IO, and PC-based controls at AutomationDirect, told us. "The availability of data in machine processes and machinery has always been a necessity in testing applications, but now data collected by process engineers and manufacturing managers is being used to improve the process in real-time."

Programmable automation controllers (PACs) have become the convergence or gray area between programmable logic controllers (PLCs) and PC-based controllers, Payne said. PACs were one of the first rack-based control systems to offer the higher processing power and enhanced memory capabilities that fit well into applications where data acquisition can be applied. The physical memory space and processing power of these devices not only can handle machine control but also can collect and analyze data and apply changes to the actual machine control in real-time. The line between PLCs and PACs is blurring. PLCs themselves are becoming more powerful and offer more of the features that PACs implemented early on.

Data collection has always been a key aspect of lab testing applications, but now the trend is toward an application base that is broadening out into mainstream process and manufacturing environments. Manufacturing systems themselves have so much data to provide that, once an engineer has an opportunity to collect the data, it often offers an opportunity to improve the process dramatically. For example, collecting real-time temperature data from a plastic injection molding machine or a tempering furnace allows engineers to identify trends, monitor the process more closely, and correlate results to product quality.

Specific applications (such as pharmaceutical or solar cell manufacturing) collected large amounts of data in the past, but with the emergence of the Internet of Things, such collection efforts seem more widespread. As more engineers realize that these capabilities are available, especially in smaller controllers (as an alternative to more expensive data logging or SCADA software), they are taking advantage of capabilities being built into the controllers themselves.

Data logging and storing large amounts about the manufacturing process itself is another target for these systems. These controllers now typically implement inexpensive memory devices such as an SD card or a removable USB drive, which typically offers 16 or 32 GB of storage on the controller itself. In these applications, machine controllers were previously limited by the restricted memory space in the controller and an inability to expand that memory or store on an external device.

Now that it is becoming the standard for industrial control, Ethernet networking will provide a potent solution for even more sophisticated data analysis applications. But it will be interesting to see how machinery builders can leverage this process data into a higher level of useful analysis.

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