Buzzwords. Love them or loathe them, some are more than mere marketing. Some are key game-changers. In the case of “IT-OT convergence”, what does it really mean and why might it be the main enabler towards smart, multi-energy ecosystems.
While everyone has heard of “IT” or Information Technology, far fewer have heard of “OT”. Indeed, many professionals working in the OT field haven’t heard of the term! Operational Technology (OT) encompasses all technology that acquires data from, and computes outcomes for, industrial equipment. Whereas IT is concerned with “data”, OT is concerned with “things”. And those things can be anything, from individual pumps and sensors through to large assets such as power plant, heat pumps, and so on.
Author
Stuart Johnston, Director of Solutions and Engineering Projets, SIG.
About
IT-OT convergence.
When multiple worlds collide.
Until now OT professionals have resisted integration with IT systems which are seen as frequently changing and as posing a potential risk to critical OT infrastructure. The operational technology world is risk-averse, preferring stability and availability of its critical infrastructure through isolated, proven technology choices.
Traditionally OT professionals would automate assets such as a pumping station using PLCs. This is something they’ve done very well for many years, and advanced PLCs allow robust control of expensive assets for operations and maintenance teams.
But add in new requirements such as, say, machine learning combined with predictive maintenance, alongside augmented reality (AR) maintenance, and traditional OT technology doesn’t have the firepower to do the job.
IT-OT convergence is the means by which IT power can be integrated into the OT domain. It opens up a whole new world of analytics, edge computing and capabilities until now unavailable with typical OT technology, bringing the power of the IT world to the OT domain in order to make OT smarter. And it’s about sharing OT data with the IT world to gain new insights and exploit new opportunities within the operational business such as mobile apps for teams, to develop new revenue streams and profit from mutualised technology platforms.
At the same time as IT-OT convergence comes another disruption, namely IoT, the Internet of Things. Isn’t IoT and OT the same thing? Well, not really. Whereas OT typically consists of equipment hard-wired to a PLC, IoT technology generally communicates through a wireless service to a server outside of the OT domain. IoT can be a cheap and fast means of getting data from the field without making costly changes to OT infrastructure such as modifying PLC data tables, communication libraries, SCADA configurations and so on.
If the OT world is to exploit the potential of Industrial IoT, as well as the opportunities of analytics, machine-learning and AR, there must be convergence somewhere. And that “somewhere” needs to make it easy to move computing power between the IT domain and the OT edge depending upon circumstances.
Beyond IT, OT and IoT : Towards a multi-energy ecosystem.
IT:OT convergence and the arrival of IoT means that removing silos, sharing data and moving computing power to where it’s needed will become the new norm.
It also means reinforcing IT and OT security in order to secure the entire data chain, end to end.
The strategic choice of an IoT platform, co-existing alongside OT infrastructure and enterprise IT systems, allows for the rapid convergence of data from the IT and OT worlds while allowing IoT devices to be added to the mix, giving engineering teams the flexibility to develop smarter infrastructure as well as adding smart capabilities to existing, legacy assets.
The advantages of IT-OT-IoT convergence are manifest. While many would stop here, for us it represents the first step towards concepts such as multi-energy ecosystems. Indeed, an integrated platform could be adequately applied not only to diverse energy networks (electric, drinking water networks, waste water networks, district heating and cooling infrastructure) but also to many concomitant elements such as PV generation and storage as part of such an ecosystem.
Enabling these distinct elements to communicate together will stimulate their synergies, while the addition of flexible cloud and edge computing will boost their intelligence and open the opportunity towards a distributed, future-proof architecture.
Implementing IT:OT convergence strategy at SIG
Within its new Smart City division, SIG has brought its IT and OT teams under one roof. Together these teams have evaluated joint criteria for the deployment of SIGs future IoT platform which will allow an IT, OT and IoT approach to solving engineering problems using a unique, consolidated data platform.
Currently SIG is performing a detailed evaluation of a potential platform and has embarked on testing several use cases including predictive maintenance algorithms for the monitoring of key industrial assets, the management of microgrids for future smart multi-energy districts, as well as Emobility management.
Glossary
PLC : Programmable Logic Controller. A rugged industrial computer designed for processes such as manufacturing or industrial plant requiring high reliability controls and regulation.
Machine learning : the ability to automatically learn and improve without being explicitly programmed by a human.
Predictive maintenance : as opposed to scheduled or periodic maintenance, predictive maintenance uses failure models and real-time data from equipment to predict failure or degradation of equipment and thereby optimise lifetime and maintenance operations.
AR : augmented reality. As opposed to VR or Virtual Reality, AR in the industrial context combines images of the real world with additional data such as sensors readings, plans and maintenance instructions to facilitate operations.
Cloud computing : storage and processing capability hosted on remote servers rather than on physical servers within a business location.
Edge computing : local processing capability such as an industrial gateway PC permitting the processing of data locally, close to industrial assets, instead of sending high volume data to the cloud.
SCADA : A high level supervisory system for industrial processes, allowing the storage and display of real-time data for the operation of industrial assets.
About the author
Stuart Johnston
Director of Solutions and Engineering Projets, SIG
Stuart Johnston is director of Solutions and Project Engineering at SIG, Geneva’s multi-energy utility company.
An engineer in electrical and electronics engineering, he is focused on transforming SIGs engineering towards delivering multi-energy solutions for SIGs industrial assets as well as developing new solutions for the intelligent management of energy within Geneva’s smart neighbourhoods.