Sustainability in industrial processes has become increasingly critical as stakeholders seek tools to guide informed decision-making. This study introduces an integrated multi-criteria decision-making (MCDM) framework to address uncertainties in prioritizing sustainable industrial processes. The methodology combines the hierarchy best-worst method (BWM) to determine the weights of criteria and sub-criteria and an interval reference point technique for calculating dual synthetic sustainability indexes. These indexes include the weak synthetic sustainability index (compensatory) and the strong synthetic sustainability index (non-compensatory), enabling robust comparisons among alternatives. The proposed approach incorporates aspiration (acceptance) and reservation (desirable) points to account for uncertainties, providing a flexible mechanism to evaluate sustainability. A case study involving five energy storage technologies demonstrates the framework's feasibility and efficiency for assessing sustainability across economic, environmental, and social dimensions, which often interact with technological, political, and cultural factors. The findings suggest the framework’s potential as a valuable tool for policy-making and public communication, particularly by aggregating diverse criteria into a comprehensive sustainability index. Key advantages of the developed method include its ability to handle data uncertainties through interval numbers and its dual-index approach for comparative analysis. However, a notable limitation is its inability to address conflicting preferences among stakeholders, such as investors, engineers, and governments, whose priorities may diverge. Despite this, the framework offers a significant advancement in sustainability-oriented decision-making, enabling the selection of optimal industrial processes under complex, multi-dimensional criteria.
