Materials Management AI Digital Twin Co-Pilot for a Global Energy Co

Challenge
The client, a major petroleum exploration and production company, faced significant operational risks stemming from material management complexities:
- Maintaining consistent availability of crude oil, natural gas, and other critical materials was essential, as disruptions could cause costly operational shutdowns and revenue loss.
- Volatile material pricing required precise and proactive management to maintain profitability.
The company sought Mahusai Global Partners’ (MGP) expertise to develop a sophisticated solution capable of accurately modeling and managing supply-demand dynamics in real time.
Solution
MGP delivered an advanced AI Digital Twin Co-Pilot that significantly enhanced the client's ability to forecast, simulate, and manage the complex supply and demand of critical production materials:
- The digital twin accurately simulates supply-demand behaviors specific to offshore rig operations.
- It continuously updates simulations through real-time data integration, refining accuracy over time.
- The AI-driven solution facilitated deeper collaboration among the client's teams, enabling strategic planning based on robust, predictive insights.
Technology
- Frontend: ReactJS
- Backend Framework: Django REST
- Visualization and Analytics: PowerBI
- Simulation Optimization: Gradient-based simulation optimization algorithms
Results
Following deployment, the AI Digital Twin solution delivered substantial operational improvements:
- Enhanced supply chain reliability, significantly reducing the risk of operational disruptions.
- Improved profitability through more precise and proactive management of volatile material costs.
- Strengthened collaboration and strategic alignment among teams, driven by highly accurate predictive insights.
The client recognized the solution as transformative, empowering them with the capability to dynamically and efficiently manage critical materials, positioning them ahead of industry volatility and challenges.
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