“International studies estimate that only around five percent of the data generated in production actually gets analyzed in depth,” says Dr Rolf Birkhofer, Managing Director of Endress+Hauser Digital Solutions. “That finding closely matches our own experience. Even though Endress+Hauser’s measuring devices have had digital communication capability for years now, the vast majority of our customers have yet to exploit this option.” There are many reasons behind the reticence, including the decades-long life span of process plants and field instrumentation, the fact that those plants often contain components from numerous suppliers, and the strict safety standards and regulations in force across many industries. Given such an environment, convincing customers to adopt new technologies involves bringing some cogent arguments to the table.
INDUSTRY AT A TURNING POINT
And yet there are areas of industry where change is afoot, says Birkhofer. The latest generation of smart instruments can supply a wealth of supplementary data alongside their actual measurements, including information on the sensors and processes themselves. There are technologies that provide a secondary channel for rapid, secure data transfer from the field right up to corporate level that is completely distinct from process control in the plant itself. Furthermore, a host of projects have already demonstrated how this data can be turned into useful information and valuable knowledge. “Digitalizing process plants is beginning to emerge more and more from the confines of pilot installations and small-scale projects,” Birkhofer says. And, he adds with conviction, “We are at a turning point.” For plant operators, it’s all about efficiency, security and quality in the face of competitive pressure and a general shortage of skilled workers. It follows that there is an enormous number of potential use cases. Analyzing data at the level of individual measuring points can already bring significant benefits. But the data generated from instruments and processes only reveals its true value after central aggregation, be that in a cloud application or edge computing system. Aggregation brings scalability to data gathering and processing, with individual use cases no longer requiring their own dedicated software. A further possibility is to link data from the field with other data sources such as weather forecasts and ERP systems, all in real time.
VIRTUAL AND PHYSICAL WORLD
A particularly exciting prospect is to combine multiple data sources using artificial intelligence. “Big data applications can glean highly complex insights in fractions of a second, given the right data inputs,” says Florian Falger, Market Manager at the Endress+Hauser Level+Pressure Innovation Lab. One of the team’s activities is finding ways to precisely determine maintenance intervals for measuring instruments and entire plants with the help of specialized algorithms and artificial intelligence. Thus they are laying foundations for something that many companies in the process industry want: predictive maintenance. “Large chemical plants, for example, operate around the clock,” Falger explains. “Even planned maintenance is a costly undertaking. Predictive maintenance would help to minimize the plant downtime involved and avoid unscheduled outages, as well as reduce workload and costs.”
