An engineering-oriented multi-attribute decision framework for industrial product design under heterogeneous evaluations

Industrial and production engineering design decisions often require selecting product schemes under heterogeneous criteria and multidisciplinary expert judgments. This study proposes an engineering-oriented multi-attribute decision framework to improve robustness, transparency, and interpretability under mixed qualitative–quantitative information and inconsistent preferences. The framework combines preference similarity analysis for aggregating heterogeneous expert evaluations, divergence-based consistency checking between subjective and objective assessments, and optimization-based weight adjustment for decision stability. Grey Relational Analysis is used for alternative ranking, while Jensen-Shannon divergence and the Sparrow Search Algorithm calibrate subjective weight contributions adaptively. A sports wheelchair design case for older adults demonstrates applicability in balancing ergonomics, manufacturability, structural performance, and usability. Comparative and sensitivity analysis results demonstrate the feasibility and relative stability of the proposed framework under the current case conditions, providing a practical decision-support tool for engineering design selection under heterogeneous evaluations.