Metaheuristic Method of Decision Making Based on an Expert Analysis of Leakage Losses in Pneumatic Systems

Industrial pneumatic systems consume significant energy in manufacturing, with leakage losses being a major inefficiency. While previous studies highlight the value of systematic leak detection and maintenance, practical decision-making often lacks structure. This study explores minimizing leakage in bottling plants while reducing component replacement costs. The guiding hypothesis is that metaheuristic optimization can generate Pareto-optimal solutions that balance these two conflicting objectives. Leakage audits were performed in 12 Bulgarian bottling facilities, identifying 2,112 major leaks (>5 l/min) using ultrasonic detection. Data from compressors, leakage volumes, and electricity rates were used to assess energy and financial losses. Four component groups—push-in fittings, FRL units, air grippers, and valves—were responsible for over 50% of the total leakage, equating to 76,228 l/min or 503,836 kWh in monthly energy waste. A metaheuristic Pareto-ranking method was applied to prioritize component replacement, balancing cost and efficiency. The findings demonstrate the value of datadriven tools in industrial maintenance, supporting cost reduction, sustainability, and improved competitiveness in pneumatic system management