predictive maintenance framework that works across different kinds of sensors. It begins with prioritisation using Pöyry’s RAMS (Reliability, Availability, Maintainability, Safety) methodology, to assess and prioritise the most relevant potential causes of failure. This RAMS approach means the system will focus on the most important data. Tomorrow’s barriers will be the evolving

relationship between humans and machines: we must learn when to trust machine decisions, how to monitor and when to take back control, and how to augment machine learning with humans’ experience and knowledge from beyond the data. For policymakers, it may also require changes to the way with think about regulation, as the lines blur between utilities and tech companies. Yet for all of this, the biggest barrier will

Stephen Woodhouse, chief digital officer at Pöyry, outlines the barriers to embracing the digital age, and offers examples of how, and why, we must break them down


on’t work harder; work smarter – this old adage is taking on new

significance as digitalisation transforms our economies, and we stand on the precipice of a global productivity revolution. Yet, while this transformation will free

us from a great deal of wasted time, it will also require us to change the energy industry. In the future, we will all be required to learn new skills and change the way we work – quite fundamentally – to adapt to this emerging reality. This requires workforces to change their

cultures and mindsets, while also learning new ways of working. This is no small task. Yet it is vital, because those who succeed will find themselves at a competitive advantage. Digital applications in energy have the

potential to transform the sector, by delivering greater efficiency throughout the entire supply chain, by revolutionising companies’ relationships with their customers, and by unlocking the potential for deep decarbonisation through automating flexibility to match production patterns of renewable energy. The earliest digital breakthroughs are in predictive asset maintenance, improved forecasting and real-time monitoring, and digital tools that aim to attract and retain customers. Drones and UAVs for remote inspections, as well as process mining and text mining are also helping to improve efficiency. Digital twins allow ‘what-if’ and predictive analysis to be performed on virtual representations of physical assets. Artificial intelligence is unlocking value


almost everywhere it is applied. While still a nascent technology,

predictive asset maintenance is becoming one of the more mature digital technologies in the energy sector. Today, predictive maintenance is at the cutting edge, but tomorrow it will be part of a much bigger system. We are still at the cusp of what the Industrial Internet of Things (IIoT) can do. The guiding star for all “industry 4.0”

technologies will be data. The data that these IIoT sensors gather will enable companies to identify and resolve problems remotely, allow engineers to deploy their time more efficiently and, eventually, machine learning might help plants automate simple engineering jobs. It will also allow plant owners to gain insights into their own operations and identify how assets can be used more productively. Energy companies are still only at an early stage in exploiting digital technologies and data streams, such as machine learning applied to rich data sources. However, this future is not yet here. To

reach this point, we need better access to clean, accessible data streams and we need to better identify where to focus our efforts. We also need to get around practical barriers like the interoperability of these sensors. Although the limits are expanding fast, constraints on processing power, data storage and algorithms mean that the 80:20 rule still applies to data analytics. It is these practical considerations that led Pöyry to co- develop Krti 4.0, a machine learning

The Krti 4.0 framework gives decision-makers real-time information on the best and the most effective operating and maintenance options for their OT systems

be ourselves. Today’s engineers have learned their trade in the last few decades, yet the skills required of them will change in the coming ones. In an interconnected, data-driven world; engineers will find they are required to be software and hardware engineers, and even drone operators, as much as they are required to be power engineers. Knowledge and information will be treated as a precious company resource and will be managed and maintained. This will require cultural transformation.

Companies that adopt a forward-looking posture will steal a march over companies that are slower to adapt. Just as tech start-ups are currently challenging the status quo in transport and retail, they will challenge engineering too. All of this means those of us who are

working in the energy sector can no longer consider ourselves discrete from technology experts. We must understand both worlds. Becoming ‘digital-first’ means weaving digital into the fabric of what we do – not simply seeing it as something that is bolted on. What’s more is that this revolution is

happening hand in hand with another one – decarbonisation. It will be digital technologies that facilitate decentralised generation, load balancing and demand- response. Traders are already using AI based forecasting and algorithmic trading to help them get ahead of their competition in energy markets, and digital tools are being used to help companies attract and retain customers. It is this final element which makes the

revolution inevitable. The energy industry simply will not continue as it is. Change is often unsettling, but it is happening, whether we like it or not. So, if you haven’t started the journey to a digital future yet – start today.



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