Analysis of Emerging Engineering Technologies for Sustainable Industrial System Based on Fuzzy Z-Number Linguistic SPC-RS-MAIRCA Models

Abstract The assessment of emerging engineering technologies for sustainable industrial systems requires complex decision-making processes to identify the most and least effective alternatives. These alternatives include renewable energy integration, advanced robotics and automation, additive manufacturing with sustainable materials, Internet of things-enabled smart manufacturing, and artificial intelligence in industrial automation. This study proposes a novel framework based on a fuzzy Z-number linguistic symmetry point and a criterion rank-sum-driven multi-attributive ideal-real comparative analysis method to evaluate such technologies. The model incorporates averaging and geometric operators formulated with Sugeno–Weber norms to process fuzzy Z-number linguistic information effectively. Finally, the applicability and robustness of the proposed approach are demonstrated through comparative examples that highlight the relative superiority and sustainability of the evaluated technological options.