Risk-Informed Performance Optimization of Waste Heat Recovery Systems: A 47-System Empirical Study with Statistical Validation and ROI Analysis
Keywords:
Waste Heat Recovery; Risk Priority Number; Quantitative Risk Management; FMEA; Predictive Maintenance; ROI Analysis; ANOVA; Industrial DecarbonisationAbstract
Waste Heat Recovery (WHR) systems play a key role in improving industrial energy efficiency and reducing emissions, but their performance is often limited by thermal, mechanical, corrosion, operational, and financial risks. This study develops a quantitative risk assessment framework for WHR systems using a modified Risk Priority Number (RPN) approach, normalized to a 1–5 scale. The framework is validated through empirical analysis of 47 operational WHR systems across five industrial categories over a 36-month period, with a total of 1,410 component-level risk evaluations. The weighted mean heat recovery efficiency was calculated as 68.3 ± 3.95%, while the overall risk index averaged 3.51. Implementation of structured risk management resulted in a 48% reduction in maintenance cost index, compared to a significant increase observed in unmanaged systems. Economic analysis based on site-level data shows a return on investment (ROI) of 312%. Statistical validation using one-way ANOVA (F(4,42) = 16.95, p < 0.001) confirms significant variation in risk profiles across system types, highlighting the importance of system-specific risk strategies. The proposed framework demonstrates measurable improvements in operational reliability, cost efficiency, and decision-making, providing a practical and data-driven approach for risk management in industrial WHR systems.
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Copyright (c) 2026 Om Kale, Tushar Bagade (Author)
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