5 %
reduction in energy and emissions costs
AI-Driven Process Optimization for Energy Efficiency
Industrial process optimization
Multi-constraint logistics algorithms
Predictive modeling for manufacturing
Large-scale industrial data analysis
Integration of AI with existing industrial systems
Customized solution development for industry-specific challenges
reduction in energy and emissions costs
achieved in less than a year
revenue company transformed
A leading global steel manufacturer partnered with Sudolabs to revolutionize their production processes through AI, aiming to reduce energy consumption and emissions while maintaining product quality.
The steel industry faces dual pressures of environmental concerns and rising energy costs. Our client's complex logistical planning was entirely human-operated, leading to inefficiencies in resource management and energy usage. They needed an innovative solution to optimize storage logistics and annealing processes, areas critical to both cost reduction and environmental impact.
Sudolabs conducted a comprehensive analysis of the client's processes and historical data. We developed two key solutions:
1. An advanced AI-powered storage management system that automates and optimizes the planning of steel coil combinations and annealing batches, significantly improving furnace utilization. This system considers multiple steps ahead and adheres to numerous complex rules, far surpassing human capabilities in efficiency and consistency.
2. A data-driven analysis of furnace operations, providing actionable insights and recommendations for optimizing temperature curves in the annealing process. This analysis identified potential areas for improvement and offered specific recommendations for empirical adjustments, laying the groundwork for future enhancements.
These solutions were designed to work in tandem, addressing both immediate efficiency gains and long-term process improvements.
Our AI-driven approach yielded a 5% reduction in energy and emissions costs, with ROI expected within a year. This success demonstrates the transformative potential of AI in heavy industry, paving the way for more sustainable and cost-effective steel manufacturing.
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