Risk Management Innovations through Neural Network Integration in Automated Boiler Combustion Systems

In the early decades of the twenty-first century, the application of artificial intelligence has been expanding across all sectors of society, including industrial energy systems. This paper emphasizes the significance of integrating artificial neural networks into boilers with automatic firing, as part of a research project currently in its fifth year of experimental validation. The implementation of neural networks in such systems has demonstrated promising results in the domain of risk management, particularly through the prediction of system malfunctions and their proactive elimination via software interventions. The application of AI-based solutions in boiler control not only contributes to the reduction of environmental impact but also enhances operational safety by preventing accidents that may endanger human health and cause material losses.