Data gathering, organizing, coordination and processing software is evolving so quickly that the reports, predictions, simulations and possible options it generates are basically becoming extensions if not integral parts of real-time process control. Plus, data analytics are getting an added boost from overlapping tools such as advanced process controls (APC), digital twins and artificial intelligence (AI) that can make them even more useful.
“In the past 10 years in the process industries, we’ve seen data analytics used in a more functional way to monitor efficiencies, most notably downtime tracking on specific machinery and production systems,” says Steve Beck, senior chemical engineer at Huffman Engineering Inc., a CSIA-certified system integrator in Lincoln, Neb. “These analytics, often seen through SCADA control, are being used more effectively to analyze the overall equipment effectiveness (OEE), including downtime caused by things like mechanical and electrical problems. When a plant is looking for solutions to common issues on a specific machine, analytics reflective of performance are invaluable.
“Not all systems are completely one thing or another, although virtual and cloud-based are becoming more prevalent. Cloud-based systems equal easy access to data, but can also introduce cybersecurity concerns, so you really need to be working with a qualified, better yet certified, system integrator to understand and alleviate those concerns. As the evolution of data analytics has grown, accessibility to more and more data has become both more prevalent and more cost-effective than ever before. That’s an especially great benefit of cloud-based analytics. The ability to get larger amounts of data faster is a competitive advantage for anyone if they know how to make strategic use of that data.”
What to do with data?
Beck reports that most companies are seeing the trend toward cloud-based analytics, and many are spending big-budget dollars to activate the data in their systems. “This is encouraging and exciting to watch,” adds Beck. “There is a word of caution to those who may simply want to jump on the bandwagon to improve processes in this way: you want to develop a plan for how to use the data once you have access to it.
“Occasionally, a company will spend the money to upgrade their systems without a plan to effectively use it. An effective plan is well worth the time. What you don’t want is to put in a powerful system and let it sit there without any strategic analysis working for you. Also, make sure you’re gathering actionable data rather than sifting through the painful and pointless. Start from the end and work your way backwards in terms of what insight you’re hoping to generate. Then place priority on understanding what the system can do for you and manage your time to allow the insight to help move your business forward. An experienced system integrator can help with that education process and make the transition smooth as well as a powerful tool in your business arsenal.”
Finally, Beck adds that data analytics will become more precise and move swiftly toward more predictive analytics. “AI will enable us to automate and generate results and solutions for things we don’t even know about yet,” says Beck. “We’ll definitely see a move toward better forecasting and get more sophisticated at extrapolating great insight on a whole host of things relating to industrial and utility production.”
