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A fuzzy logic modelling of predictive maintenance in rotating machinery

Prommachan W., Surin P., Srinoi P., Pipathattakul M.

Archives of Materials Science and Engineering

2024

Vol. 126, nr 1

15--22

Purpose: The study aims to investigate and assess the application of Fuzzy Logic to construct a predictive maintenance model for rotating machinery. Design/methodology/approach: The research uses a mixed approach, with both quantitative and qualitative approaches, and are four main steps: 1) surveying and analysing existing predictive maintenance techniques; 2) determining appropriate expert assessment criteria for predictive maintenance techniques; 3) vibration analysis by the experts; 4) evaluate the performance of rotating machinery with fuzzy logic. Findings: The result of the study will be used to build a rotating machinery predictive maintenance model, which is very similar to the traditional method. The obtained data showed that the efficiency of the rotating machinery and the vibration level were compliant with the standard ISO 10816-3. Thus, such data can be planned for maintenance to maximize benefit. Research limitations/implications: Future research should optimise the model and add additional modules for automatic data collection. The production monitoring system should help collect data by considering downtime, predicting the functional service life of rotating machinery, etc. Practical implications: The proposed model can be used in small water pumps in order to perform predictive maintenance. The conceptual framework was tested, particularly with rotating machinery. Originality/value: The fuzzy logic model is described as the fuzzy of a process with linguistics for greater clarity.