Multistage Fuzzy Decision-Making for Dynamic Sustainability Improvement

The development and deployment of robust technical solutions for sustainability improvement have become increasingly critical in response to growing environmental and social pressures while maintaining economic viability, particularly in industrial systems that require multi-stage technology implementation. Identifying such solutions requires the systematic treatment of significant uncertainties that affect sustainability-related decision-making. Among these, epistemic uncertainty, arising from incomplete or imperfect knowledge, is inherently subjective and, in principle, reducible. Fuzzy set theory provides an effective and well-established framework for representing and managing epistemic uncertainty in sustainability analysis. In this work, a fuzzy decision-making framework is proposed to support multi-stage technology development and deployment for dynamic sustainability performance improvement in industrial systems. The framework integrates comprehensive sustainability assessment with fuzzy representations of epistemic uncertainty to enable consistent comparison of alternative strategies at each implementation stage. It identifies the most appropriate strategy at each stage while ensuring alignment with long-term sustainability objectives. The proposed approach functions as a decision-support tool for guiding adaptive, stage-wise technology deployment under uncertainty. A case study of a nickel electroplating system is presented to demonstrate the applicability and effectiveness of the methodology.