A decision support tool for waste heat to heat recovery technologies in industrial sectors

Industrial waste heat-to-heat recovery directly repurposes thermal energy for on-site duties, avoiding conversion losses and fuel consumption. This paper presents a decision-support tool that screens and ranks thirteen heat-to-heat technologies: indirect heat exchangers, recuperators/regenerators, heat pipes, thermal storage, air preheaters, heat pumps, absorption heat pumps, and mechanical vapour recompression, using uniform criteria weights, performance, economic, and environmental indicators. The framework filters options based on temperature class and industrial application, normalises datasets, and uses a weighted-sum multi-criteria analysis with visual heatmaps to clarify trade-offs. For a rubber facility with medium-temperature exhaust and low-temperature demand, the tool shows that heat pumps and conventional exchangers are preferable due to their readiness, low integration risk, and minimal CAPEX/OPEX in cost-focused scenarios. Technical emphasis elevates heat-upgrading options, as heat pumps improve recoverable temperature lift and site coverage, but require higher investment. Environmental emphasis prioritises heat pumps and long-lived equipment, achieving the largest CO 2 -intensity reductions per delivered kilowatt-hour of useful heat. Results highlight that optimal selections depend strongly on stakeholder priorities and boundary conditions. Conventional exchangers deliver fast, low-risk savings; upgrading technologies unlock deeper decarbonisation where a temperature gap exists. The framework enables auditable, site-specific short-listing, clarifies the rationale behind rankings, and supports early engagement between process owners and integrators. The results show a 20.8 % annual reduction in useful energy demand. Savings narrow during demand peaks and decline during extended periods of low load. • Web-based decision-support tool for screening waste-heat-to-heat recovery across sectors and temperature classes. • Converts different data (efficiency/COP, TRL, CAPEX/OPEX, lifespan, installation, CO 2 ) into normalised, comparable scores. • Interpretable MCDA with equal/economic/technical/environmental scenarios; outputs as heatmaps, bar charts, and rankings. • Case study (rubber-sealing line): 20.8 % annual energy reduction; recovered-heat band ∼ 0.30 – 0.50 MW th during operation. • Transferable framework intended for additional sectors; site engineering and pilots recommended for integration.