<![CDATA[Type selection of grinding machines and air classifiers is a critical issue in dry grinding–classification process design, particularly under uncertain environments where statistical data are unavailable and expert judgments dominate decision making. This study proposes a fuzzy group decision-making framework integrating fuzzy equivalence clustering, fuzzy score function with decision makers’ weights (FSFDMW), and TOPSIS to enhance selection reliability. First, main criteria are identified using fuzzy equivalence clustering. Then, an n-dimensional fuzzy environment is constructed to determine the weights of decision makers and criteria. Finally, a TOPSIS procedure based on fuzzy score functions is applied to rank alternatives. Application to the dental gypsum grinding–classification process shows that the impact mill achieves the highest priority value (0.742), while the MS type air classifier obtains the highest priority value (0.96417). The proposed framework improves decision accuracy while maintaining computational simplicity.]]>
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