Using k-NN Artificial Intelligence for Predictive Maintenance in Facility Management

This article presents a study on the application of k-Nearest Neighbor (k-NN) machine learning algorithm for predictive maintenance in facility management. The implementation is crucial elimination unforeseen breakdowns, optimization operational efficiency, and reduction costs. k-NN was employed dataset comprising diverse factors to predict probability machine's malfunction. findings our case demonstrate that possesses favorable qualities scenarios, owing its straightforward versatility generating accurate outcomes. Nevertheless, supplementary measures beyond selection models are necessary actualize potential fully. procedures encompass creation dependable data framework, continual surveillance refinement models, assessment more intricate modelling methodologies. study's results indicate exhibits promise as valuable tool maintenance, thereby offering significant benefits management strategies terms efficiency effectiveness.