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What's leading IIoT transformation in 2017

The rise of data has led to a different kind of decision-making for industrial professionals. IDC predicts that by 2020 the data derived from connected devices will reach 44 zettabytes, and even over the past year we’ve seen IIoT drive new levels of productivity, efficiency and asset availability for organizations worldwide.

At its core, this industrial transformation is all about the connected asset. Connectivity has enabled organizations to derive more productivity and value from machinery and systems, breathing new life into aging infrastructure. As we look to 2017 and beyond, we’ll see IIoT continue to revolutionize organizations, with the biggest transformations being led in three key areas:

1. Industrial digital twins

A fairly new concept for the IIoT, digital twins will transform the way organizations operate and evaluate asset failures in the coming years. A digital twin is essentially a computerized companion to a real-world entity, with the goal of bringing the physical and digital worlds closer together. In an industrial setting, a digital twin could be a physical asset like a gas turbine, or a highly complex system within a chemical plant. The huge amounts of data collected by sensors on these objects make it possible to represent their near-real-time status in their digital twin.

Similar to the way retailers create digital profiles of their customers and use data gathered from their online shopping habits to predict what and when they will buy, organizations can create profiles of each machine — and each part that comprises it — in order to make smarter decisions about maintenance, better optimize performance and reduce unplanned downtime.

2. Asset performance management

Asset strategies have existed for many years as components of engineering design, maintenance and inspection plans, and condition monitoring, but what has shifted more recently is the integration of risk principles and easier access to asset data. The focus of asset performance management (APM) is to consolidate all types of reliability data into one centralized, intelligent system for deeper analysis that drives smarter decisions. In the beginning, much of this data was generated by maintenance and work order histories; plants were completely dependent on various personnel entering data, causing inaccuracies and gaps in information.

Today, however, with the advent of connected devices, we have more accurate data on assets than even just a decade ago. Machines are getting “smarter,” and are able to provide very detailed data about their health and performance. So instead of having too little accurate equipment information, organizations now struggle with too much. Looking ahead, we’ll see APM technology play a greater role in compiling vast disparate equipment and process data in a way that can supply relevant and timely information to organizations.

3. Industrial cybersecurity

In October, hackers launched some of the largest cyberattacks the internet has ever seen, powered by something new: an army of over one million hacked IoT devices. According to reports, hackers used two networks — commonly referred to as botnets in the hacking community — made up of around 980,000 and 500,000 hacked devices, mostly connected cameras.

While these attacks weren’t launched at an industrial organization, the risk associated with these types of cyberattacks and the likelihood of them occurring will only increase in the future. This is largely due to the unique security challenges associated with operational technology, which has become more connected in the past decade. Industrial organizations are challenged to protect not only their data, but also their physical assets and control systems, because today’s threats are more sophisticated and targeted than ever before. Fortunately, emerging technologies help critical infrastructure build in layered defense, similar to how network security is layered in the enterprise space. In the coming months, expect to see industrial organizations prioritize cybersecurity tools and strategies in order to prepare for what is essentially a matter of “when” and not “if.”

The rapid pace of industrial transformation and IIoT is not likely to slow down anytime soon with smarter software creating an IIoT ecosystem worldwide. Organizations must prioritize a strategy focused on asset connectivity, or risk falling behind.

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