Data-driven preventive maintenance for a heterogeneous machine portfolio
نویسندگان
چکیده
We describe a data-driven approach to optimize periodic maintenance policies for heterogeneous portfolio with different machine profiles. When insufficient data are available per profile assess failure intensities and costs accurately, we pool the of all profiles evaluate effect (observable) characteristics by calibrating appropriate statistical models. This reduces compared stratified that splits into subsets uniform treats same.
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ژورنال
عنوان ژورنال: Operations Research Letters
سال: 2023
ISSN: ['0167-6377', '1872-7468']
DOI: https://doi.org/10.1016/j.orl.2023.01.006