{"id":"W2122519530","doi":"10.1016/j.ijpe.2006.04.015","title":"Reliability consideration in the design and analysis of cellular manufacturing systems","year":2006,"lang":"en","type":"article","venue":"International Journal of Production Economics","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":63,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Cellular manufacturing; Reliability (semiconductor); Computer science; Process (computing); Reliability engineering; Integer programming; Routing (electronic design automation); Plan (archaeology); Mathematical optimization; Engineering; Algorithm; Embedded system; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005004568,0.00005215517,0.0001234151,0.0002580998,0.00001417287,0.00003496835,0.00007674874,0.00002532365,0.000002366234],"category_scores_gemma":[0.0000526435,0.00004371485,0.0000333658,0.00004498759,0.0000242738,0.0001945316,0.000005034335,0.00007637207,1.64221e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008603578,"about_ca_system_score_gemma":0.000008751033,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001914922,"about_ca_topic_score_gemma":0.0000073808,"domain_scores_codex":[0.9993874,0.00003483728,0.0004022171,0.00006524901,0.00006744107,0.00004282883],"domain_scores_gemma":[0.9995512,0.00008401152,0.0001890811,0.00006941886,0.00009820716,0.000008032146],"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":[0.00001266494,0.00001390722,0.0003953047,0.000006565227,0.00008505394,0.000001163829,0.00007895545,0.9979986,0.0004232658,0.0006474071,0.00003240112,0.0003047003],"study_design_scores_gemma":[0.00034909,0.00003080774,0.02497939,0.0000224489,0.0001929324,0.00005805459,0.0002270593,0.9059186,0.06048883,0.007042318,0.0005571694,0.0001333265],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5638126,0.00009448517,0.4353032,0.00009203231,0.0005890129,0.00005504837,0.000002462172,0.000005163633,0.00004599904],"genre_scores_gemma":[0.9937655,0.0001739275,0.005879083,0.000004407264,0.0001553705,0.000001511823,0.000007607729,0.000004341929,0.000008197498],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4299529,"threshold_uncertainty_score":0.178264,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01136817189655232,"score_gpt":0.2074073209604336,"score_spread":0.1960391490638813,"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."}}