{"id":"W2040405051","doi":"10.1016/j.ress.2010.12.023","title":"Condition based maintenance optimization for multi-component systems using proportional hazards model","year":2011,"lang":"en","type":"article","venue":"Reliability Engineering & System Safety","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":267,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Condition-based maintenance; Component (thermodynamics); Preventive maintenance; Reliability engineering; Condition monitoring; Dependency (UML); Engineering; Work (physics); Maintenance actions; Unit (ring theory); Computer science; Operations research; Mathematical optimization; Systems engineering; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001115942,0.0008645217,0.001469828,0.0006056014,0.0003630235,0.0007023591,0.001230457,0.0008614591,0.002515575],"category_scores_gemma":[0.002175747,0.0006067149,0.0008781051,0.0005575699,0.000497514,0.001145283,0.0007088445,0.0007742845,0.000145014],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006998185,"about_ca_system_score_gemma":0.0009146114,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006757489,"about_ca_topic_score_gemma":0.003247695,"domain_scores_codex":[0.9996039,0.000139445,0.00001413325,0.00007216918,0.0001195366,0.00005083991],"domain_scores_gemma":[0.9991211,0.0006498921,0.00006585328,0.00003885284,0.00009756571,0.00002669138],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003551913,0.00001694698,0.00009923439,0.00002372204,0.00001619561,0.00001290587,0.000009772577,0.9942302,0.0004235077,0.001208189,0.0001091983,0.003814595],"study_design_scores_gemma":[0.000004636373,0.000009324984,0.00004795773,5.402677e-7,0.00000367742,0.000001929093,0.000001010266,0.9992287,0.00006234505,0.0006172491,0.00002136675,0.000001250846],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06396613,0.0003514606,0.9326673,0.0001529079,0.00003627245,0.00006133186,0.00008787151,0.0002841146,0.002392704],"genre_scores_gemma":[0.9582708,0.0001796141,0.03840057,0.00002592536,0.00002418635,0.0001209592,0.000113817,0.00005745959,0.002806644],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006757489,"threshold_uncertainty_score":0.01343632,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0249531931011578,"score_gpt":0.2221492380271124,"score_spread":0.1971960449259546,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}