AI FOR ENERGY TRANSITION & RESOURCE MANAGEMENT
Implementation of the Just-in-Time Philosophy in Coal Production Processes as an Approach to Supporting Energy Transition and Reducing Carbon Emissions
In the context of Poland's commitments under the European Union's climate policy, including the European Green Deal and the Fit for 55 package, as well as the decision to ban imports of hard coal from Russia and Belarus, ensuring the stability of the domestic market for energy commodities is becoming a key challenge. The response to these needs is the Coal Platform concept developed by the KOMAG Institute of Mining Technology (KOMAG), which aims to integrate data on hard coal resources, production, and demand.
Key Impact Metrics & Our AI Solution
The most important problem is not the just-in-time (JIT) strategy itself, but the lack of accurate, up-to-date data and the high technological and organizational inertia on the production side. The JIT strategy assumes an ability to predict future demand well in advance, which requires advanced analytical tools. Therefore, the Coal Platform project analyses the use of artificial intelligence algorithms to forecast demand and adjust production to actual market needs.
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GHG Emission Reduction by 2030 (EU Target)
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Variables in Demand Forecasting Model
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Accuracy of Top Forecasting Models
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Hard Coal Demand Reduction (2010-2030)
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
JIT + AI
Core Innovation: Dynamic Resource Management
Integrating the just-in-time (JIT) philosophy with AI-driven forecasting and scenario-based planning within a cloud-ready Coal Platform architecture, enabling dynamic resource management and compliance with decarbonization targets.
JIT for Energy Transition Macro-Framework
Minimize Inventories
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Demand-Driven Production
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Timely Data Integration
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Scenario-Based Re-planning
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Robust and Scalable Cloud Architecture
The Coal Platform leverages a modular, cloud-native architecture on Microsoft Azure, incorporating distinct user access, presentation, transaction, and analytical layers. This design ensures tailored functionality for producers, consumers, and institutions, facilitating independent development, scaling, and advanced security. Real-time data processing and decision support are enabled by the analytics layer, ensuring reliable operation even under heavy loads and aligning with the just-in-time strategy for energy transition.
Challenge: Integrating disparate data sources and managing complex stakeholders in a secure, scalable, and adaptable system for strategic energy management.
Solution: Deployment on Azure Kubernetes Service (AKS) for container orchestration, Azure App Services for web portals, Azure SQL Database for structured data, and Azure Machine Learning for AI-driven forecasting. Secure API Management (HTTPS, OAuth 2.0) ensures robust integration with external mine and distribution systems.
Outcome: Enhanced operational efficiency, precise functionality tailoring for diverse user groups, and the ability to process real-time information critical for JIT strategy implementation and dynamic resource management.
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Key Variables in Forecasting Model
The core forecasting model employs a multivariate regression equation considering 12 variables, including electricity/heat production from coal, coal/alternative energy prices, industrial demand, regulatory intensity (1-10 scale), and seasonality (0.85-1.15 index). This detailed approach captures complex dynamics and non-linear responses, crucial for precise JIT adjustments.
54%
Hard Coal Demand Reduction (2010-2030)
Forecasts indicate a significant reduction in hard coal demand in Poland. From 2010 to 2030, demand is projected to fall by 54%. More immediately, between 2023 and 2030, a further 24.9% reduction is anticipated, reinforcing the urgent need for JIT mechanisms.
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~1.000
R² of Multivariable AI Model
Our multivariable AI model demonstrates significantly higher explanatory power (R² ≈ 1.000) and lower error rates compared to a simple linear time-trend baseline (R² ≈ 0.89). This confirms its ability to capture complex market dynamics and policy impacts beyond a simple decline.
Future Research & Development Roadmap
Model Validation & Scenario Testing
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Expand Variable Set (Macro, Renewables, Carbon Price)
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Optimize AI Models (Hyperparameter Tuning, Ensemble)
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Overcome JIT Implementation Obstacles
Calculate Your Potential ROI with Enterprise AI
Estimate the financial and operational benefits of implementing an AI-driven JIT system tailored to your enterprise. Adjust the parameters below to see your potential savings.
Estimated Annual Savings
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Hours Reclaimed Annually
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Our Proven Implementation Roadmap
We guide enterprises through a structured, phased approach to integrate AI solutions seamlessly, from strategy to sustainable operation.
Phase 1: Discovery & Strategy Alignment
In-depth analysis of current operations, data infrastructure, and strategic objectives. We identify key integration points for JIT and AI, defining a tailored roadmap for your energy transition goals.
Phase 2: Platform Design & Data Integration
Architecting the cloud-native Coal Platform, designing data models, and establishing secure API integrations with existing production and demand systems. Focus on real-time data ingestion and validation.
Phase 3: AI Model Development & Calibration
Developing and fine-tuning AI forecasting algorithms (e.g., ARX, FLNN) using historical and projected data. Rigorous cross-validation and scenario testing to ensure high accuracy and robustness.
Phase 4: Pilot Deployment & Optimization
Implementing the Coal Platform in a pilot environment, monitoring performance, and iteratively optimizing functionalities based on feedback. This phase focuses on achieving initial JIT synchronization and measurable impact.
Phase 5: Full-Scale Rollout & Continuous Improvement
Scaling the platform across the enterprise, providing comprehensive training, and establishing governance for ongoing monitoring, maintenance, and adaptive re-planning to meet evolving market and policy needs.
Ready to Transform Your Energy Operations?
Harness the power of AI and Just-in-Time principles to optimize your coal production, meet decarbonization targets, and secure your energy future. Our experts are ready to partner with you.
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