Technology and energy saving potentials in the industrial sector are key data that policy-makers rely on to drive decision-making. A literature review reveals a distinct discrepancy between general potential estimation and detailed design studies. The former relies principally on top-down conceptual approaches based on temperature levels of the processes’ thermal requirements, while the latter aims at mathematically optimized solutions for specific technologies in specific processes under specific economic conditions. This work attempts to close this gap by proposing a bottom-up method for potential estimation of energy saving measures. To this end, a generalized optimization framework was developed which aims at generating a database of optimal solutions which are independent from most economic and environmental input data. By fixing these data, the optimal solution for the same process type in different countries and under various criteria can be identified in the database. The method also increases accessibility of optimization techniques by providing the solution database which then requires limited input parameters and background knowledge to provide expert guidance toward optimal utility integration. The method was applied to the dairy industry, highlighting that energy saving potentials can be achieved through heat recovery and integration of heat pumps, mechanical vapor re-compression, and co-generation units economically favourable especially in Japan and Switzerland.