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ABB participated as a Silver Sponsor at ARC Advisory Group’s 22nd India Forum (July 10-11, 2024) titled Accelerate Transformation in the Age of AI, Open Automation, and Sustainability. Keeping in sync with the Forum’s theme Rajesh Ramachandran, Global Chief Digital Officer, Process Automation, ABB, spoke about Advancing Sustainability and Productivity with AI. With the advancement of technology, industry is moving from automated (Industry 3.0) to autonomous operations (Industry 5.0). ABB has been leading all the five industry revolutions. Over the past three years, there has been a noticeable shift towards maximizing business value via available digital applications.
Last year, Rajesh’s presentation was about driving digital business outcomes using industrial AI at scale; now there’s been a paradigm shift, and the focus is on sustainability. For most organizations, sustainability has become the license to operate now. All boardroom conversations begin with sustainability and then move on to performance, productivity, and reliability. “So it has become very important, not only to meet our own sustainability targets and commitments, but also help our customers drive their sustainability targets,” said Rajesh.
This blog summarizes the key aspects of his presentation on advancing sustainability and productivity with AI. The entire presentation is available here.
The Sustainability Focus
Sustainability is a vast topic and often cannot be navigated through exclusively. Sustainability, performance/productivity and asset reliability are sometimes competing priorities. So, technology that can help optimize all three aspects has to be used. In this context, Rajesh spoke about the “new child” in the AI paradigm - Generative AI. He explained how ABB has co-innovated with its customers to bring GenAI to industries to optimize the goals for sustainability, productivity, performance, as well as reliability. Sustainability has emerged as the fulcrum of business operations in terms of energy efficiency, carbon footprint, and creating a circular economy. And the shift is also to remote digital operations. ABB provides lifelong support to its customers and its services division comprises 45 percent of its business. So remote digital operations have become a critical offshoot and almost 60 percent of the services team work remotely. Asset performance management has to be done holistically by linking it with sustainability and energy efficiency. Hence, the solution deployed must encompass all these aspects - how it is going to impact the operational performance, the asset life as well as the sustainability. And the technology paradigm also is shifting, especially in the industrial IoT and AI, but also the whole idea of the Generative AI fusing into the industrial applications has been making a big difference.
Strategic Priorities
Organizations are undergoing huge transformation with three mandates to sustain and be relevant: operational performance, energy transition and sustainability, digital growth and productization, which becomes to some extent, content or the solution to achieve the first two priorities or achieve more than what you have. This provides the context to scale AI for advancing sustainability and productivity.
The three secular shifts are: decarbonization, resource efficiency, and security of supply. To meet these requirements ABB offers automation, electrification and digitalization. Rajesh spoke about how AI can be further scaled using Generative AI capabilities. From the diagram above it is clear that the left side is what has been used for over a decade for predicting and analysis. Whereas the right side is about generating content - Generative AI. “There is no old and new AI, both have to be combined to get the required solution,” said Rajesh.
Unlocking the Power of Generative AI
Generative AI is reinventing industry by extending capabilities for safer, smarter, and more sustainable operations. In this context, Rajesh spoke about the collaboration between ABB and Microsoft that will help industry executives, functional specialists and shopfloor engineers with real-time actionable insights for better decision making and increased productivity. The approach must be three dimensional and meet the combined objectives of sustainability, productivity, and reliability. One of ABB’s customers commented that if we “talk only about sustainability we’ll be running out of business.” Implementing Generative AI along with Analytical AI in industrial settings presents several challenges, such as complexity of technology, integration with existing systems, scalability, data management etc. These challenges highlight the need for a systematic approach and robust framework to successfully implement Generative AI in industrial settings. Further, Rajesh spoke about how the use cases are identified and how the three targets are optimized through models and processes. The graphic below explicitly shows how ABB helps customers achieve their objectives. This is fundamentally what ABB sees as the value of using the new Generative AI along with the analytical AI for advancing both sustainability and productivity.
Panel Discussion
Sharing Rajesh’s views during the interactive panel discussion.
How ABB promotes GenAI to its customers:
ABB’s focus in not to reinvent AI core technologies, but as a technology and industrial leader for decades, it is known for making sense of leveraging AI to solve some of the most complex industrial problems. We go with domain expertise and pre-integrated domain AI solutions and discuss the problems with the customer/s. We have a digital value engineering team that understands the problems that need to be solved on the maintenance side/operational performance/process/sustainability. The focus is on how to optimize all three elements.
About the shift to 5G:
There’s been a significant shift to 5G, especially among Europe’s discrete manufacturers. OT data centers are needed to collect data, train and facilitate bi-directional communication; for this, excellent connectivity is needed. ABB has been working with Ericsson to bring 5G into the AI and IoT world. Where we see a real need for this is in the autonomous operations for marine vessels.
Lifecycle cost and emotional value:
Data and domain context is crucial to combine processes and AI to get the right outcome. AI can be used not only to predict and optimize, but also to find out the data quality and contextualization of metadata. We do that in our Genix platform. The lifecycle cost of AI is justified as the ROI is higher. AI can never be a pilot it will always be a co-pilot. Automation plus human-centric AI will make operations autonomous.