THE FIRST THING ENTERPRISES WANT TO DO IS CAPTURE DATA AROUND WATER, ELECTRICITY, GAS FLOW RATES, AND FROM THERE, YOU CAN BEGIN OPTIMISATIONS.
DISRUPTIVE TECH
From a macro perspective, energy markets have two challenges. The demand for energy is increasing dramatically. Just in data centres alone, it is like three times. On one hand, we have this incredible increase in demand for energy, while a significant part of the population has no access to power.
At the same time is the need to have more sustainable energy, which is decarbonisation and alternative energy sources. So how do we meet the energy demand and at the same time, decarbonise and diversify the energy sources that we have.
The big opportunities for enterprises are through what AVEVA calls its handprint, which is the ability to help customers reduce their carbon footprint, and help them become more sustainable, which is a focus for AVEVA. There are an enormous amount of use cases around for using less water, air, steam, gas, electricity, and decarbonising.
THE FIRST THING ENTERPRISES WANT TO DO IS CAPTURE DATA AROUND WATER, ELECTRICITY, GAS FLOW RATES, AND FROM THERE, YOU CAN BEGIN OPTIMISATIONS.
out, drawing the piping, the tool itself will make a recommendation on the right way to have it and they can make decisions on the cheapest routing using different pipes and materials, and the most efficient design.
The first thing most enterprises want to do is capture data around water, electricity and gas flow rates, and then from there, you can begin to drive optimisations. And this is where you start to apply AI analytics. What are the reasons we are consuming so much water on this sort of steam turbine? And then the analytics can point to ways to reduce the consumption.
These are well documented cases and AVEVA has got cases where turbines can save 100,000 gallons of water purely by running an optimisation. AVEVA can reduce
CO 2 emissions by optimising the fuel that is burnt.
What is industrial AI?
AI is a headline topic and is probably the most transformative thing that will affect industries in the next decade. Specifically for the industrial sector it is a set of tools and techniques can be used to drive lots of different optimisations across different disciplines and different markets.
AVEVA is currently using Generative AI on authoring and design tools to let designers for power plants, offshore oil rigs, whatever it may be, design things in a safe and sustainable way. And what Generative AI does, it looks at the patterns of all previous designs and makes clever assumptions about how to optimise future designs.
If I am a designer and I am trying to connect four tanks with four pumps, rather than me drawing the diagrams
On the authoring and design side, AI and Generative AI is used to help designers create sustainable, safe, optimised engineering initiatives.
If you think about AI and the production operations side, lots of amazing things have been happening there. That is a more mature market. AVEVA has been doing AI there for almost two decades. This is the realm of predictive analytics and prescriptive analytics.
AVEVA looks at equipment like turbines or compressors, measures all the variables and looks for anomalies and patterns in that. These different behavioural changes in the equipment are sent to operators and maintenance technicians as notifications, that there might be a problem with this equipment. That is predictive analytics.
Prescriptive analytics becomes not just notifying someone that there may be a problem but advising them on what might be causing the problem so that they can actually take corrective actions.
Roadmap for implementing industrial AI
AVEVA creates templates for different types of equipment that exists in manufacturing, but all plants and all operating environments are unique. This is where customers themselves, or a system integrator will help the customer tweak the models a bit based on their operating conditions and their equipment.
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