How Industrials Are Leveraging AI To Meet Sustainability Targets

These days it is not just about what you produce but rather how you produce it too. For the global energy and industrials complex doing so sustainably is a vexing problem. The solution may be, and in many cases already is being, provided by artificial intelligence (AI) and advanced analytics.

For Jim Chappell, Global Head of AI and Advanced Analytics at industrial software and consulting group AVEVA, it’s all about joining the dots between the desire for an improved throughput with sustainability objectives, and what you are likely to get as a result is a vastly improved low carbon landscape.

“In that endeavor AI is a vital and purposeful tool. The possibilities are infinite – from AI driven carbon capture to physics-based simulation, predictive asset optimization to streamlining processes for a green hydrogen future or making the power grid more resilient,” Chappell noted at the recently concluded AVEVA World 2023 Conference in San Francisco, U.S.

Ultimately what AVEVA and its peers are attempting to do is provide the software underpinnings or the digital backbone of a sustainable industrial ecosystem, one that’s connected, time sensitive, data responsive, but with human oversight and fail-safe mechanisms built into it.

If it sounds complex, then imagine swapping age-old analog industrial processes and manual information gathering in favor of the same information being delivered digitally and processes near instantly executed via algorithms operating on the basis of the collected and captured data.

The company’s system is called AVEVA Connect upon which it builds its own software solutions, and claims its customers are embracing AI technology that suits their operations, and admittedly, their budgets.

For the uninitiated, there are two primary AI pillars in the industrial complex. The first is Generative AI, or AI capable of generating media / text using generative modeling, and subsequently learning from it to generate new models or executable data that may have similar but often improved characteristics.

The second is Predictive AI or the use of data and analytics based machine learning for the identification of patterns (e.g. past events and processing) and make forward predictions (e.g. about future events and processes, suggested improvements in throughput, best times for maintenance).

Both can be brought into play via what AVEVA describes as its “gateway to an unlimited world of data analytics” including anonymized learning from third party analytics. And all of it with one objective in mind – helping companies achieve net zero faster.

“The AI journey of energy and industrial companies is really just beginning. It isn’t just that processes and approaches are changing, so has the scope of our ambition as an industry partner. For AVEVA and our customers, its not about closed software anymore, rather about open ecosystems,” Chappell added.

Those customers aren’t being coy either about turning to AI in their march to net zero. AVEVA CEO Caspar Herzberg was routinely found rubbing shoulders at AVEVA World 2023 with decision makers of companies his software outfit is providing solutions to.

Companies as diverse as Henkel, Yinson and Mitsubishi Power appeared pretty keen to discuss the benefits of AI and big data across their five key corporate pillars – operations, maintenance, forecasting, revenue and collaboration.

Beatriz Blanco, Platforms and Applications Senior Manager, at Mitsubishi Power said: “Is it worth it? Yes, that question has already been answered in the affirmative. Such software and tools help you scale effectively. The technology at our disposal, developed in partnership with vendors such as AVEVA, has been constantly improving for what is now a process efficiency journey of over 10 years for us.”

And according to a recently commissioned Total Economic Impact (TEI) study conducted by Forrester on behalf of AVEVA, customers who invested in its solutions – over three years – saw an improvement in operational efficiency of 1-2%.

That has resulted in average cost savings of $405,000, and an ROI of 466% with payback in less than six months. It all bottles down to industrial basics, according to Chappell.

“AI makes things that are already possible, quicker, and frees people up to deal with more pressing issues in the value chain, rather than working on paper problems. It can also serve as a protective mechanism in risky processes. But the biggest potential of AI is to help achieve net zero by continually improving corporate efficiencies and returns in tandem.”