Finding Big Data Opportunities in Industrial Automation

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Here we are in the world of Big Data and all of its possibilities. Just look at all the data we have available to us: production, maintenance, distribution, personnel, finances – real-time, historical and predictive. There is more data being collected more quickly and from more sources than ever before. We are swimming in it.

So, now what? Now that we’ve gathered all of this data, what does it mean to us? Personally, having reams of integers, floats, strings and timestamps in my hands doesn’t make me feel any smarter. As the old adage goes: Data is not information. Data without context offers no insight. Data without structure reveals no opportunities. How do we get from data to information? How do we get from information to knowledge? And how do we get from knowledge to action?

Finding the Anomalies

The US Department of Defense employs a process known as Activity-Based Intelligence (ABI) to find useful details in large sets of data. For example, in 2013, when two bombs exploded near the finish line of the Boston Marathon, investigators immediately had at their disposal hundreds of hours of surveillance footage, cell phone photos, and time-stamped video from dozens of angles. To manually review all of this media would require thousands of man-hours – time that is obviously not available in a situation like this.

To make use of this constellation of data, investigators were forced to find a way of automating the investigation. They decided to establish a specific set of details they wanted to locate in all of these photos and videos. Namely, they were looking for any individuals at the scene of the bombing who were not running away or looked unafraid. The behavior recognition technology existed, so it was a simple matter to enter a set of variables into a program and to let the software review the footage in an effort to find the activity that matched these variables. Soon, two suspects were revealed.

While it would have been nearly impossible for human analysts to review all of this footage in a timely fashion, investigators discovered that Big Data could in fact be very useful if combined with a mechanism to compare and contrast the thousands of data points being reviewed.

A similar technique is now being employed in cancer research. A so-called “Big Mechanism” has been created to review the vast and complex medical records of cancer patients that have been established over the years to find overlapping patterns or consistencies that can lead to a new understanding of root causes or precipitating circumstances. By automating the research, we are now able to analyze data sets of much greater size and complexity than would be possible using only human analysts.

Can Similar Techniques be Employed in Industrial Automation?

Today’s industrial enterprises find themselves in a situation similar to those described above. Huge amounts of data are being recorded and opportunities for improvement are known to exist, but how do we know what to look for and how do we find it? The same sort of ABI employed by the DoD may well have a place in the commercial world.

If we can review our historical process data to define the circumstances surrounding certain conditions (unplanned downtime, spikes in energy consumption, etc.), we may be able to recognize repeated patterns or anomalous activity related to these specific circumstances, thereby enabling us to take action to correct the situation before it happens again. By finding the data that stands out from the rest, detailing the characteristics of that data, and looking for those characteristics elsewhere, we may be able to pinpoint causal relationships that were previously obscure or misleading.

On the flipside, the same techniques can be employed to define the circumstances surrounding periods of extended productivity or energy efficiency. The same techniques used to discern the cause of deficiencies can be used to optimize asset performance and improve the quality and efficiency of our processes.

By creating analytic mechanisms aligned with the principles of ABI, we are able to create a safer, more efficient, more productive work environment. Of course, some of this runs counter to the way most of us are programmed to think. We tend to put more stock in consistent, reliable information, while discounting the anomalies. ABI encourages us to find the anomalies and focus on them.

The key to navigating the world of Big Data may not lie in the massive set of data, but in the tiny subset of data that teaches us about the abnormalities or anomalies we find. Look for the data points that stand out from the rest and ask yourself why. Consider the circumstances surrounding the collection of that data; can we map certain plant floor conditions to specific results?

Thus far, the Big Data movement has been a combination of hype and optimism, with very little practical value in daily operations. Some companies are finding ways to take advantage of the opportunities, while others have fallen behind.

Can you find the opportunities?

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A Case for Mobile Devices in Automation

One of the fastest-growing and most widespread trends in the HMI and SCADA software realms is that of mobility. Namely, how can we – or should we – take advantage of mobile devices in automated work environments?

There are those who have concerns about security. Are mobile devices secure enough to allow them to access sensitive process-related data? And if so, how much access should they have? Read/Write access? Read only? Should they be limited to a certain subset of data? And, if so, how can our control user access to ensure that users only access what they are authorized to see? Will these devices open holes in the network that allow malicious applications access to sensitive controls?

While some of the security concerns are certainly valid, the benefits of mobile devices are impossible to overlook, and the truth is that many of the security concerns are not inherent in the devices themselves, but in the way that the HMI/SCADA system and network infrastructure are configured.

Consider some of the pains that mobile devices can help eliminate:

  • A field operator must call the control room to ask for the reading on certain piece of equipment (i.e. valve, switch) he/she is looking at or manipulating.
  • A field operator must call the control room to confirm whether a certain piece equipment has truly been shut down for maintenance work because it sounds like it is still running.
  • A field technician dangerously works on a live line because the control room has shut down the wrong line!
  • A field operator must call the control room to describe equipment schematics because he/she has no access to an HMI or drawings on the floor at that moment.
  • A field operator must call the control room to pull out the manual for a piece of equipment because the panel on the one he/she is looking at is different from the others he/she is used to.
  • A field operator must describe over the radio what he/she is seeing – lights on a panel, leaks, etc.
  • An operator must take a check-list out to the field, return to the control room and enter the results into a form or spreadsheet, or into the control HMI.
  • Constant calling back and forth between field and control room when testing or calibrating a measurement or control element.

A mobile device can be used to remotely monitor processes and equipment, view drawings or manuals, review an online checklist, enter information into a form, even adding value as a tool for remote collaboration.

When properly configured and combined with role-based user access control, a wide array of new possibilities are revealed. The time saved in the field can now be used to perform other tasks or implement programs for optimization. A safer, more productive workforce is a very real benefit, and that’s not something that business owners or managers will take lightly.

Are mobile devices a part of your business model? If not, it may be time to review your processes and make room for the future.