Virtual, Augmented, & Real Reality: Digital Technology Driving IT-OT Convergence

Posted by Dan Miklovic on Wed, Jun 29, 2016 @ 10:12 AM

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SCO_Images_1.jpgFor virtually every category of technology supplier serving the industrial market today, from automation companies to infrastructure providers to enterprise software providers, the topic of IT-OT (Information Technology - Operational Technology) convergence or IT vs OT is a dominant theme of their solutions marketing.

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At LNS Research, we have written about the drivers of IT-OT convergence as well as the hype around the topic. With so much being written about IT-OT one would think that there is a little more to be said about the topic. It would seem the only thing left to observe would be which suppliers are actually enabling IT-OT convergence. Unfortunately, that is not quite true. There still remains a lot of confusion about the nature of IT-OT convergence and what it really means. In fact, there is a considerable debate about if IT and OT are really going to converge, in that plant engineering and operations (OT) and IT staffs often seem as alienated as ever. One recent article in an automation journal even speculated if it was possible given the disparities between the two functions in most organizations. Much of the debate centers on the cultural and philosophical difference between the classic IT roles supporting the financial aspects of the business and the operational imperatives of real-time response to daily challenges.

Convergence is Already Occurring

While there are examples of organizations that have isolated the two worlds of IT/OT, the fact is that IT-OT convergence is already occurring and like all things technical the rate of occurrence is accelerating. Ever since MS Windows made its way to the plant floor in the 1980’s and Ethernet networks with TCP/IP began dominating at the end of the 1990’s, the convergence has been happening. Some of the most enlightened organizations realized this around the turn of the century and started creating teams that melded the IT and process control OT roles. A recent InTech magazine article goes even further, explaining why users are demanding commercial IT –type software now. Much of it has to do with the pace of improvement and the rate of innovation that exists in the commercial software space. Analytics is an area where this is particularly evident. Predictive Maintenance (PdM) has traditionally been the domain of specialized solution providers. Today, the analytics engines behind traditional Big Data platforms are increasingly being used to provide PdM capabilities to organizations that adopted those tools initially for customer relationship management (CRM) functionality. Having developed expertise in using these tools, and with the tools leveraging machine learning to make modeling simpler, many organizations are finding they no longer need expensive proprietary applications to gain PdM benefits of the proprietary solutions.

The Digital Twin will be the Tipping Point for Driving Further Convergence

In both the smart product and Smart Connected Asset world the concept of the Digital Twin, which provides for a virtual representation of a product or a plant that is used to produce goods or services, is becoming a key Digital Transformation mechanism. When you bring together the digital virtual model with the real product or physical asset, the opportunities created in the augmented reality (AR) environment are just too great to ignore. One common example is providing maintenance technicians with virtual 3D X-ray images of the equipment they are servicing to aid in inspection and repair. Having the knowledge of exactly how a piece of equipment is configured, what parts are installed and the details current to the as-maintained level will greatly improve the effectiveness of those technicians. For most companies, maintenance activities are considered an operational issue, but it becomes clear that having the Digital Twin maintained to exactly match the physical asset is also an IT issue.

Similar examples related to quality modeling and operational risk management issues, such as deciding whether to accelerate production pace vs potential reliability/quality impacts, and equipment performance simulation vis-à-vis new product manufacturing processes, all bring IT heavy requirements to operational management activities. Driven by the Digital Twin concept, as it relates to consumer oriented products and as the basis for new opportunities related to selling additional services and capacity instead of actual products in the B2Bsector IT-OT convergence, is not only a given it is an imperative.

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Tags: Risk Management, Big Data, Information Technology, Digital Transformation