KBR has deployed its artificial intelligence platform, KBR INSITE®, across Indorama Corporation’s ammonia and olefins process units in Nigeria, introducing plant-wide monitoring and decision-support capabilities aimed at improving operational efficiency, equipment reliability and energy consumption.
The platform combines physics-informed artificial intelligence with historical and real-time plant data, KBR’s process engineering expertise and site-specific operating knowledge. It is designed to monitor asset performance continuously, identify optimisation opportunities, detect emerging process and equipment anomalies, and support root-cause analysis.
KBR INSITE also integrates Orbital AI, developed by UK-based Applied Computing. According to KBR, the integration has produced a world model for ammonia that learns cause-and-effect relationships across an entire plant, rather than identifying patterns in data alone. The company said this approach can shorten deployment times between contract signing, data handover and the availability of a live operational model.
AI platform targets energy use and plant reliability
The system provides plant personnel with near-real-time operational insights and recommendations. Its capabilities include evaluating operating scenarios, identifying process constraints and supporting decisions intended to increase throughput and asset availability.
Hari Ravindran, Senior Vice President and Global Head of Technology Solutions at KBR, said: “Our relationship with Indorama spans decades, and this deployment will support their mission to transform operations through engineer-grounded AI.”
He added: “KBR INSITE will help Indorama evaluate operating scenarios and act on clear, traceable recommendations generated from physics-informed models and site-specific data, helping increase plant throughput, improve asset availability and support more reliable, efficient operations.”
Deepu Sivdas, Chief Technical Officer at Indorama Eleme Fertilizer & Chemicals Limited, said the platform provides insights into the performance of the company’s ammonia and olefins plants through near-real-time analysis of operating parameters.
“KBR INSITE provides comprehensive insights into the performance of our ammonia and olefins plants through near-real-time analysis of key operating parameters. It helps identify tangible opportunities to optimize energy consumption, increase throughput, detect operational constraints and develops systematic root cause analysis—enhancing plant reliability, efficiency and profitability,” Sivdas said.
He added that the platform combines physics-based models with data analytics and explains the technical reasoning behind its conclusions.
“Like a seasoned specialist, it combines physics-based models with data analytics and explains the technical reasoning behind each conclusion, giving our engineers the confidence to act on its recommendations. Backed by KBR’s expertise as a process licensor, we are already seeing practical benefits in our day-to-day operations,” he said.
The company has not disclosed quantified savings in energy consumption, increases in throughput or other performance metrics resulting from the deployment.
KBR expands AI platform deployment to Egypt
KBR is also extending the platform to another industrial customer. Egypt Basic Industries Corporation (EBIC) has signed an agreement to implement KBR INSITE at its facility, with the system expected to become operational by the end of 2026.
The agreement adds to KBR’s efforts to expand the use of physics-informed AI across industrial and energy operations. The company said the deployment strategy builds on its investment in Applied Computing, announced in March 2026, and its collaboration with the technology developer to combine AI capabilities with KBR’s process technologies and engineering expertise.
KBR’s investment announcement described a multi-year joint development agreement to create AI products for the energy sector, integrating Applied Computing’s Orbital model with KBR’s technology and domain knowledge. The partnership is intended to develop applications across asset operations, capital projects and the assessment of emerging technologies.
Bioenergy Business Analysis
The Indorama deployment illustrates how physics-informed AI is being applied to complex industrial facilities, where operational decisions depend on interactions among process conditions, equipment performance and energy use. Unlike systems that primarily identify statistical patterns, physics-informed models incorporate engineering principles to help explain the relationships behind their recommendations.
For ammonia and petrochemical plants, applications such as anomaly detection, process optimisation and root-cause analysis could support more efficient use of energy and improve equipment availability. However, the commercial significance of the Indorama deployment will depend on measurable results, including changes in energy intensity, production throughput, unplanned downtime and maintenance requirements.
KBR and Indorama have reported practical operational benefits, but have not published performance data to quantify the impact. The planned EBIC implementation will provide another opportunity to assess the platform’s deployment across industrial facilities.
The development is relevant to the wider energy and industrial technology landscape, but it is not a bioenergy project. Its relevance to the sector is indirect, through the potential role of digital optimisation in improving the efficiency of energy-intensive industrial operations.
Related: Read about Sahamco’s Dakhla green ammonia project.
