Data Analytics Is More Evolutionary Than Revolutionary

Sept. 6, 2018
Successful IIoT deployment is focused largely on IT and operations teams working together. An integrator can help broker that discussion and get technologies working that you might already have in place.

Using data analytics in manufacturing automation can provide opportunities for improved operations and performance optimization. The crucial step to considering an initiative focused on data analytics in manufacturing is examining the current state of the plant’s information system. Key to that is adopting the Industrial Internet of Things (IIoT) as a plant-wide strategy.

Typically, an IIoT initiative starts with an infrastructure talk. In some cases, the “things” are already securely connected to a plantwide network, in which case we can jump directly to an information discussion. But often, the data that analysts are after is not easily accessible. Some of these networks are in fact subnetworks that were designed to be inherently isolated to limit the scope of what can talk to what.

A challenge for integrators is helping customers understand the opportunities around IIoT—including that IIoT is more evolutionary than revolutionary. Integrators have been connecting devices and harvesting data for decades in the industrial automation field, long before the concept of the IIoT and data analytics came along. Any seasoned control engineer can most likely attest to the fact that we’ve always connected smart things to perform a function, with the valuable byproduct being a wealth of data. But where IIoT is different lies in how we collect, compute and move the data and to where.

In a true IIoT deployment, the cloud (public or private) is the ultimate destination for the data, where it coalesces with other disparate data to provide context and create actionable information such as data analytics.

Part of any successful IIoT deployment is focused less on the technology and more on the ability of the information technology (IT) and operations technology (OT) departments to work with the data—and each other. Facilitating IT/OT convergence from the people perspective is challenging, but very rewarding when an integrator can help bridge that gap.

Facilitating IT/OT convergence applies not just to manufacturers, but also to integrators. We decided many years ago to undergo our own version of IT/OT convergence as automated controls began relying more heavily on common IT infrastructure. We saw very clearly that the performance of our systems depended directly on this infrastructure, so we made a business decision to bring IT professionals on staff with strong backgrounds in data centers, security, switching, routing, virtualization, and more broadly IoT. These experts give our OT organization unique IT credibility when working with IT departments, which in turn helps break down barriers.

A recent project demonstrates the importance of breaking down these barriers. One of the more challenging IT/OT convergence experiences dealt with a large national manufacturer with dozens of plants across the country. The challenge was that corporate IT had its own vision for IoT enablement through data sharing between the enterprise and manufacturing, but the plants over time had adopted their own methods, some of which were quite unorthodox and convoluted.

The solution was to deploy a best-practices industrial demilitarized zone (DMZ) at one plant, which is one of the key elements of IIoT in a manufacturing setting. This was a project that started on the OT side, but ultimately had to cross into the IT realm to create a hardened DMZ between the office network and the plant floor network. We started with “the talk” regarding secure and scalable infrastructure and had to broker many conversations with corporate IT and manufacturing OT on how the firewalls and DMZ server resources would be set up.

There was a lot of education that had to occur on both sides, but what we ended up with was a mutually agreed upon design that ultimately became the corporate IT standard for data access. It was the best outcome possible because the design had valuable input from both sides and has started them on the right path in their digitization journey.

You might already be on a path toward using data analytics and not even be aware. Your plant automation systems might already have some of the fundamental building blocks in place but need some updating. Recruit the services of a qualified system integrator to help have “the talk” about IIoT and create the robust path to using data analytics.

Daniel C. Malyszko is director of operations for Malisko Engineering Inc., a certified member of the Control System Integrators Association (CSIA). See Malisko Engineering’s profile on the Industrial Automation Exchange.

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