Abstract

Hospitals’ daily operations have become increasingly dependent on medical devices. However, the occurrence of faults is inevitable. Therefore, it is crucial for hospitals to make timely fault diagnoses and enact the corresponding measures and improvements. This paper proposes a novel concept lattice method for the intelligent diagnosis of medical device faults. To minimize the influence of uncertain factors, fuzzy sets are used to accurately express relationships between concepts. First, the occurrence frequency and severity of each fault type are extracted based on the collected information. Then, the fuzzy formal context of occurrent faults and known faults can be constructed. Next, the corresponding fuzzy concept lattice is established and visualized using a Hasse diagram. Finally, the similarity between the concept lattices is calculated and used for fault diagnosis. Here, the weight factors are determined using the decision-making trial and evaluation laboratory (DEMATEL) method. A comparative analysis is performed to show that the proposed method uses simple calculations and is highly accurate.

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