Digitalizing compressed-air system operations management to improve industrial energy efficiency

Compressed-air systems are major electricity consumers in industrial plants, accounting for approximately 10 - 30% of total production electricity depending on the industry. Many systems are still operated conventionally without continuous monitoring or data analytics, resulting in substantial energy losses from leakage, heat, idle operation, and inefficient pressure control. This study analyzes compressed-air energy consumption, introduces a digital monitoring and energy-management model based on the Industrial Internet of Things, cloud computing, and artificial intelligence, and evaluates its economic, technical, and environmental benefits. Digital monitoring enables real-time performance assessment, early fault detection, leakage identification, predictive maintenance, and optimized equipment scheduling. The proposed approach can reduce energy waste, operating costs, and greenhouse-gas emissions while improving system reliability and industrial competitiveness.