ABB and Microsoft collaborate on AI
ABB and Microsoft are expanding their long-standing partnership by working together to integrate the Microsoft Azure OpenAI Service into the ABB Ability Genix Industrial Analytics and AI Suite. Together, the companies will deploy generative AI technology to help industrial customers identify insights previously hidden in their operational data. Improved data capture and troubleshooting will enable significant improvements in efficiency, productivity, asset reliability, and operational safety, while simultaneously reducing energy consumption and environmental impact.
More Productivity Expected
After its launch, the new application, named Genix Copilot, is expected to enhance the user experience with intuitive features and streamlined exchange of context-based data across processes and operations. The new application will be able to provide industry leaders, specialists, and operations technicians with actionable real-time data, thus forming a basis for better decisions and increased productivity. ABB engineers anticipate that the insights gained could extend the lifespan of assets by up to 20 percent and reduce unplanned downtime by up to 60 percent.
Advantages for Environment and Safety
Furthermore, the solution will provide advanced monitoring and optimization data on industrial greenhouse gas emissions and energy use, helping customers meet their sustainability and energy goals. Genix Copilot will also make it possible to capture the knowledge of users and make collaborative decisions across different roles — with a clear focus on protecting data and knowledge within the company.
“This is an important step in the strategic partnership between ABB and Microsoft, which will accelerate the digital transformation of the industry,” says Rajesh Ramachandran, Global Chief Digital Officer of ABB's Process Automation business unit. “Genix Copilot will support industrial customers in meeting their goals regarding sustainability, operational excellence, and improved asset performance. By implementing generative AI capabilities into ABB's digital industrial solutions, we are leading customers into a new era of AI, enabling billions of better decisions.”
Data Integration
Genix aims to unlock the full potential of data by automating the contextual integration of operational, engineering, and IT data across the entire enterprise, and by enabling advanced analytics and optimization with industrial AI. It can seamlessly scale from individual machines to plants to enterprises. Additionally, the platform can be deployed in cloud, hybrid, and edge environments as well as on-premises. Genix already leverages Microsoft Azure for integrated cloud connectivity and services.
“Companies that modernize and scale their data platforms are, in our view, best positioned for long-term success,” adds Ralph Haupter, President, EMEA, at Microsoft. “The application of advanced digital services such as Azure OpenAI Service will enable Genix to effectively manage contextual data. At the same time, we are driving forward the digital transformation that is crucial for growth and sustainable change.”
According to Ramachandran, ABB Ability Genix is a comprehensive, modular, industrial IoT, analytics, and AI platform that leverages industry-specific expertise to improve business outcomes and protects the customer’s existing investments. Companies that use Genix have been able to reduce their operating and maintenance costs by up to 40 percent, increase their production efficiency by up to 30 percent, and improve their energy and emission values by up to 25 percent. The expansion of Genix with generative AI functions is expected to further enhance these benefits, Ramachandran continues.
What does this mean?
ABB will integrate generative AI, including large language models like GPT-4, into the Genix platform and its associated applications using the Azure OpenAI Service, enabling, among other things, code and text generation as well as image recognition. The incorporation of self-learning AI can make applications more intuitive and sustainable – even if one does not know how and with which data the AI was originally trained.
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