Optimizing predictive maintenance decisions: use of non-arbitrary multi-covariate bands in a novel condition assessment under a machine learning approach

HIGHLIGHTS

• who: David R. Godoy and colleagues from the Lab, Department of Industrial Engineering, Universidad Tu00e9cnica Federico Santa Maru00eda have published the article: Optimizing Predictive Maintenance Decisions: Use of Non-Arbitrary Multi-Covariate Bands in a Novel Condition Assessment under a Machine Learning Approach, in the Journal: Machines 2023, 11, 418. of /2023/
• what: This work aimed to determine multiple covariate bands for the transition probability matrix via supervised classification and unsupervised clustering. This research has built an enriched bridge between the decision areas of and Data Science. In this study, a model is proposed that . . .
  

   

  

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