A Fuzzy Decision Support Framework for Medical Equipment Classification in Hospital Technology Management

Medical equipment classification is a fundamental step in hospital technology management, directly influencing acquisition planning, maintenance strategies, resource allocation, and infrastructure management. Traditional classification methods are often based on rigid thresholds or isolated criteria, which may not adequately represent the uncertainty and multidimensional nature of medical devices. This study proposes a fuzzy logic-based decision support model for medical equipment classification, integrating six criteria: dimensions, mobility, complexity, installation and maintenance requirements, infrastructure needs, and equipment cost. A Mamdani fuzzy inference system was developed in MATLAB R2025b to classify medical devices into three categories: Small, Medium, and Large. The model includes a graphical user interface that enables user input, automatic classification, and visualization of fuzzy membership functions and defuzzification results. The proposed approach provides a normalized output ranging from 0 to 1, allowing transparent interpretation of both classification results and associated membership values. The model contributes to more flexible and interpretable decision-making in hospital engineering and medical equipment management by incorporating uncertainty into the classification process.