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    <responseDate>2026-10-13T15:22:46Z</responseDate>
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    <identifier>10.57760/sciencedb.44342</identifier>
    <datestamp>2026-07-31T16:03:10Z</datestamp>
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  <dc:date>2026-07-31</dc:date>
  <dc:title>PRUL-MRO Reproducibility Package: Data and Code for One-Step Rolling Maintenance Support for Multiple Assets Driven by Probabilistic RUL</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.44342</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>Reproducibility package for the manuscript &amp;quot;One-Step Rolling Maintenance Support for Multiple Assets Driven by Probabilistic RUL&amp;quot;. It contains engine-level disjoint split identifiers derived from NASA C-MAPSS FD004 (149 training / 49 calibration / 51 internal test), the frozen configuration and its SHA-256 hash, all calibration candidate results, 40 formal simulation episodes per method and scenario for S0 and S5, seed-level paired statistics (bootstrap and Wilcoxon), cycle-level decision logs, the fitted weighted KNN probabilistic RUL model, and the source code, run scripts, configurations and unit tests. The original third-party NASA C-MAPSS files are not redistributed; acquisition and preprocessing scripts are provided. The environment is semi-synthetic: sensor evolution and failure endpoints come from public run-to-failure trajectories, whereas maintenance resources, costs and task processes are generated from released configurations.</dc:description>
  <dc:subject>probabilistic remaining useful life; rolling maintenance; multi-asset maintenance support; resource constraint; probability integral transform; conditional value-at-risk</dc:subject>
  <dc:creator>Liu Yong</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
  <dc:rights>https://mit-license.org</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:publisher>Science Data Bank</dc:publisher>
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