You can cite this dataset using the following DOI:
This repository has the supplemental materials for the article
Improving prescriptive maintenance by incorporating post-prognostic information through chance constraints
by Anthony D. Cho, Rodrigo A. Carrasco, and Gonzalo A. Ruz.
Paper information available here: summary.
- Uploaded instances, scenario generator, and pdf with visualization.
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MachinesLocation.pdf: Visualization of the Machines location in 2D space.
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scenarioGenerator.py: scenario maker script in python, sampling from a normal distribution for Remaining Useful Life (RUL).
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datasets.xls: contains some problem cases, each per sheet, which contains machine ID, component type ID, machine location (X, Y), Mean Time To Repair (MTTR), and RUL. A summary is provided in the following table.
Sheet name Description Components_info Component types with the Mean Time To Repair (MTTR) in hours Machine_info Machine types and their locations (X,Y) Problem_26 26 components (4 machines, 8 component types) Problem_50 50 components (6 machines, 17 component types) Problem_100 100 components (8 machines, 20 component types) Problem_150 150 components (9 machines, 20 component types) Problem_200 200 components (10 machines, 20 component types) Problem_500 500 components (20 machines, 20 component types) Problem_1000 1000 components (20 machines, 20 component types)