{"id":"W2101926044","doi":"10.1109/rams.2007.328069","title":"Joint Optimization of Inventory Control and Maintenance Policy","year":2007,"lang":"en","type":"article","venue":"","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Preventive maintenance; Corrective maintenance; Inventory control; Safety stock; Control (management); Computer science; Production (economics); Reliability engineering; Optimization problem; Inventory theory; Operations research; Holding cost; Work (physics); Operations management; Engineering; Business; Economics; Supply chain; Microeconomics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001518771,0.001479108,0.001784233,0.0008423678,0.000343338,0.001789655,0.001050276,0.001148874,0.001773483],"category_scores_gemma":[0.003901055,0.0008029692,0.0006371976,0.000884992,0.0007739109,0.001478577,0.0007425935,0.0008770963,0.000326764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001396559,"about_ca_system_score_gemma":0.002068405,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004273192,"about_ca_topic_score_gemma":0.002542746,"domain_scores_codex":[0.9989128,0.0003134132,0.00005432154,0.0002053886,0.0002337605,0.0002803492],"domain_scores_gemma":[0.9986958,0.0007032074,0.0002731093,0.00008806559,0.0001508082,0.00008902053],"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":[0.00009829758,0.0000526257,0.0004051142,0.00004062439,0.00002885713,0.00003850332,0.00001502127,0.983307,0.001428399,0.00363309,0.0002846715,0.01066783],"study_design_scores_gemma":[0.00002050745,0.00008395891,0.0004415552,0.00000479307,0.00002631655,0.00001980536,0.00001103264,0.9953848,0.0009480429,0.002740835,0.0003109982,0.000007439883],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1718744,0.001621396,0.8133636,0.0006852522,0.00008882445,0.0002039737,0.0002492298,0.0005903405,0.01132303],"genre_scores_gemma":[0.9711646,0.0003120136,0.02527505,0.00003781684,0.00002944254,0.000103026,0.00008690896,0.00003673953,0.002954494],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004273192,"threshold_uncertainty_score":0.01013273,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005637931692480186,"score_gpt":0.1966233750482447,"score_spread":0.1909854433557645,"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."}}