Abstract

The optimization of hot blast stove emissions is a crucial aspect of improving energy efficiency and reducing environmental impact in industrial processes. This study explores the implementation of an automated control system to regulate combustion parameters and minimize pollutant emissions while maintaining optimal thermal performance. By integrating real-time monitoring, predictive modeling, and adaptive control algorithms, the proposed system dynamically adjusts fuel combustion rates, air-fuel ratios, and operating temperatures. Experimental and simulation-based analyses demonstrate that such automation significantly enhances process stability, reduces NOₓ and CO₂ emissions, and optimizes fuel consumption. The findings highlight the potential for integrating smart automation technologies into hot blast stove operations, offering a pathway to sustainable and energy-efficient industrial practices.

Keywords: hot blast stove, emissions optimization, automated control system, combustion regulation, energy efficiency, air-fuel ratio

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