For better energy management, tap into your data historian
Users of energy management applications are learning that the data these applications collect can help improve the performance of production equipment and processes.
Big Data, as you may already know, is the current Big Thing in the Information technology space. A technical description of Big Data and how it can impact business operations sounds like this:
Data science and innovative analytical algorithms are helping companies improve business operations by tapping into vast amounts of data stored in disparate systems and then leveraging previously unrealized data correlations.
Stated more simply, Big Data is about finding ways of making practical use of the massive amounts of information companies create in the course of doing business, and thus is stored on the corporate networks.
Most of the buzz surrounding Big Data centers on its potential value to sales and marketing pros. Those folks are told that using advanced analytic applications to slice and dice all the information generated in the process of making sales and filling orders can give them better insight into their customers’ needs and desires. And, of course, that knowledge is supposed help the company target customers with offers that will entice them to buy more of their product or service, and make those purchase decisions sooner.
As is the case with most technology, however, developers are finding ways of applying Big Data beyond the realms of sales and marketing. We have discovered, for instance, that there are instances in which Big Data tools can enhance industrial energy management.
To a large extent, energy management technology developers have been applying the central concepts associated with Big Data for some time. They may carry such a splashy label Big Data, but many energy management applications are built around the concept of collecting and analyzing data related to energy usage, and then using data to enact processes that make operations more energy efficient.
Beyond energy efficiency
In many cases, users of energy management applications also are finding that the data these applications collect can also help them improve the performance of production equipment. Sometimes, the data also gives plant managers ideas about how to improve production processes.
In the cover story to this Industrial Energy Management supplement, Patty Solberg, director of product marketing at Powerit Solutions, makes these points, among others, as she persuasively argues that manufacturers should cease be hesitant to adopt industrial management technology. In most cases, she argues, the perceived hurdles are not nearly as difficult to overcome as they seem. And, in all cases, those who fail to adopt energy management technology are forfeiting huge financial benefits.
In our second article, Chris Davis from LinkCycle Inc.—a true Big Data vendor—explains how this technology is being used to allow commercial building managers to audit energy use solely through software, allowing them to achieve energy savings much more quickly, and inexpensively, than using traditional methods.
He also explains how industrial enterprises—given the greater complexity of their operations—can reap even greater financial regards from joining the Big Data movement.
Our final piece focuses on how to reduce energy consumption of refrigeration systems, which are among the heaviest users of energy in plants where they operate. The idea is to look at all refrigeration units as a single, integrated system. That means, as you’ve probably guessed by now, analyzing total energy use, finding the points of leakage and design methods to make the entire system more efficient.
The bottom line here is whether it’s big, medium or small, the first step in creating an effective energy management strategy, is using the data that already exists within your enterprise.
Sidney Hill, Jr., is a CFE Media Contributing Content Specialist. Edited for the CFE Media Industrial Energy Management section in February. Send comments to firstname.lastname@example.org.