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Home » Energy » Honeywell Technologies Launches New Industrial AI Platform at Nigeria’s Dangote Refinery
Energy

Honeywell Technologies Launches New Industrial AI Platform at Nigeria’s Dangote Refinery

by Emmanuel Ebube October 26, 2026
written by Emmanuel Ebube October 26, 2026
Storage tanks are seen at the newly-commissioned Dangote petroleum refinery in Ibeju-Lekki, Lagos, Nigeria, May 22, 2023. (REUTERS/Temilade Adelaja)
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LAGOS, Oct 26 – Honeywell Technologies has launched its Forge Plant Cognition industrial artificial intelligence platform at the Dangote refinery in Lekki, Lagos, as the company seeks to improve operational productivity and profitability at one of Africa’s largest refining facilities.

The platform combines Honeywell’s industrial expertise with artificial intelligence and computing technologies from NVIDIA and Dell Technologies. According to Honeywell, preliminary estimates suggest it could generate operational benefits exceeding $0.29 per barrel at the refinery, equivalent to approximately $60 million annually in gross benefits at full-capacity throughput. The company cautioned that the estimates are preliminary and not guaranteed.

Honeywell is already supporting the expansion of the Dangote refinery’s nameplate capacity from 650,000 barrels per day to 1.4 million barrels per day by 2028. The additional capacity is expected to increase the facility’s potential output and the scale of operational improvements that advanced industrial technologies could deliver.

The launch builds on Honeywell Technologies’ introduction of Forge Cognition on October 14, 2026. The platform uses agentic AI and simulation technology to help operators monitor facility conditions, assess equipment performance, anticipate maintenance requirements and optimise energy consumption.

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Forge Cognition integrates real-time digital twins with AI agents that can analyse operational data, simulate potential changes and coordinate actions across supported existing systems. Its applications include automated alarm classification, predictive equipment maintenance and energy optimisation.

For industrial facilities, the technology is designed to help teams process large volumes of equipment data and distinguish critical problems from false alarms. Its predictive capabilities can also identify emerging equipment issues before they cause operational disruptions, while digital twin simulations allow operators to evaluate changes without immediately implementing them in live environments.

Honeywell Technologies said the platform is designed to complement human expertise, with customers able to operate it in manual, semi-autonomous or autonomous modes. Operators retain control over the level of oversight and can override the system at any time.

“The physical world demands more than a powerful AI model. It requires AI to understand how systems actually operate and interact—that is where the next breakthrough is happening,” said Suresh Venkatarayalu, Chief Technology Officer, Honeywell Technologies. “Forge Cognition combines AI with operational context and engineering expertise, opening a new era of intelligent operations where AI can analyze, recommend and act alongside people.”

NVIDIA and Dell provide AI infrastructure

The platform draws on NVIDIA’s AI models and simulation technologies, alongside computing infrastructure supplied through Dell Technologies’ AI Factory with NVIDIA.

NVIDIA technologies incorporated into the platform include Nemotron open models for interpreting operational data, Omniverse libraries for physically accurate simulations, and Cosmos models and video analytics capabilities for analysing sensor data. The system also uses NVIDIA RTX PRO graphics processing units, with expansion planned to support far-edge deployments using NVIDIA DGX Spark.

Dell Technologies provides supporting infrastructure through PowerEdge XE servers, data and storage systems, cyber resilience solutions and technical services used to develop, train and operationalise AI models and agents.

The partnership reflects a broader push to apply AI beyond digital applications to physical infrastructure, including industrial facilities and buildings, where equipment reliability, energy efficiency and operational performance can have direct financial consequences.

“Physical AI is bringing new intelligence to the complex systems that run our buildings and industrial facilities,” said Deepu Talla, vice president of robotics and edge AI at NVIDIA. “Honeywell Technologies is combining NVIDIA AI and simulation technologies with its deep industrial expertise to help customers anticipate equipment issues, improve reliability and energy efficiency across the infrastructure they already operate.”

John Roese, global chief technology and chief AI officer at Dell Technologies, said the next phase of AI development would increasingly involve systems capable of reasoning and acting within real-world operational environments.

“The next wave of AI innovation will be driven by intelligent systems that can reason, learn and act in the context of real-world operations,” said John Roese, global chief technology and chief AI officer, Dell Technologies. “The Dell AI Factory provides the infrastructure and services that support Honeywell’s vision for intelligent physical operations.”

Honeywell expands its African refining presence

Beyond Nigeria, Honeywell Technologies has also been selected to support Dangote’s planned mega-refinery in Lamu County, Kenya. The project would extend the relationship between the technology provider and Dangote’s refining business into another African market.

The projects highlight the potential role of industrial automation, AI and advanced computing in the development of Africa’s refining capacity. As operators invest in larger and more complex facilities, technologies that improve equipment availability, manage energy use and reduce operational inefficiencies could become increasingly important to project economics.

For the Dangote refinery, the projected $60 million in annual gross benefits remains an estimate rather than a confirmed financial outcome. Its realisation will depend on operational performance, implementation and the facility’s eventual throughput.

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