‘Data is the new currency’

Industry experts advise manufacturers to enrich their plants with better data collection, management.


At the International Maintenance Conference in Florida in December, Bentley Systems CEO Greg Bentley talked about the expanded use of data in manufacturing. Courtesy: Bentley SystemsIt is an era of rich data in manufacturing, and the companies that can harness that data will enrich themselves and their plants.

"Data is the new currency," said Jagannath Rao, president of Siemens USA's customer service division at the 30th International Maintenance Conference in Bonita Springs, Fla., in December. "This is the future of manufacturing: machines talking to machines, robots working in collaboration with each other, machines knowing the state of their own health. It's the next level of asset analysis. This is going to be the future, and some companies already are on board."

The ability to not just collect data, but also to manage it for the benefit of both operations and end users is one of the transformative ideas discussed by three industry experts at the Reliability and Asset Performance (RAP) Talks, which were the keynote on the second day of the IMC conference.

"We all want more productivity. We want our manufacturing to be more flexible. And, of course, we want this to happen efficiently and, more important, seamlessly," Rao told about 1,000 maintenance and reliability professionals at the conference. "It all begins with data, and more data. All of our factories are connected with sensors. We collect this data. We need to transmit this data and either predict something or have it tell us trends or show us patterns about what we could change."

Greg Bentley, president and CEO of Bentley Systems, showed examples of how 3-D modeling in brownfield operations could produce reliable models of the current state of a plant and tie that data into operational models.

Bentley sees the process going beyond information technology (IT) and operational technology (OT). "We need to leverage the digital engineering model," Bentley said. "When we talk about digital engineering models, we're talking about things like schematics, 3-D models, network models. We need to go beyond IT and OT to engineering technology, or ET."

At IBM, the challenge is to make sure the data is serving its highest purpose for customers. That's not always just data for the sake of data, said Pete Karns, vice president of offering management for IBM.

"We know the data is there. Do we start with data or start with what we want to learn?" he said. "I see far too many of our clients collecting the data without understanding what it is they want to learn."

Karns said the Internet of Things (IoT) allows data to be viewed as an asset unto itself—something that needs to be studied and understood, not simply collected. "IoT is doing something differently with data than you've done before," he said. "We can talk about connectivity and millions of sensors, but it's just about doing something different with data. What we're seeing first is the types of data are there, but it's hard to work with.

"We all have biases, and we immediately use our 30 years of experience to say what we think is happening," Karns added. "Where we're moving with analytics is removing the bias. We're evolving to a much more powerful way of using the data to help us look beyond our own biases."

Rao said manufacturers need to prepare for this new era of data management-and warned that those who don't will miss a huge competitive opportunity. "By 2025, 85% of manufacturing will be connected," Rao said. "If you're not on the bandwagon, you will lose your competitive advantage." 

Jose , TX, United States, 02/04/16 08:02 AM:

We build assets that should be last at least 25 years. The money is in the operations of these assets. We've got to show the decision-makers that it works. Because it's the next quarter's earning that they are interested in, we'll have to change the immediacy. Where we've been moving into asset optimization makes sense. When you start to look at how we use technology, and its productivity, what we see is our definition of productivity. We need to change our mind set. It is NOT correct to believe because we use smart phones!!! We are doing our processes smarter or are the smartest. Technology should change our mind set and open it so we can see things are possible in different ways. After that you could say that you are actually improving your productivity
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