Using artificial intelligence to predict surface roughness in deep drilling of steel components

Journal of Intelligent Manufacturing

Volumn 23, Issue 5, 2012, Pages 1893-1902

  Bustillo, Andres ^a   Correa, Maritza ^b,c  

^a UNIVERSITY OF BURGOS   (Spain)

^b CSIC   (Spain)

^c UNIVERSIDAD AUTÓNOMA DE MADRID   (Spain)

Author keywords

Bayesian networks; Deep drilling; Minimum quantity lubrication (MQL); Supervised classification; Surface roughness

Indexed keywords

ARTIFICIAL INTELLIGENCE TOOLS; CUTTING FORCES; CUTTING PARAMETERS; DEEP DRILLING; HIGH-SPEED CONDITIONS; INPUT DATAS; INPUT VARIABLES; MACHINE LEARNING CLASSIFICATION; MACHINE OPERATORS; MINIMUM QUANTITY LUBRICATION; MOULDS AND DIES; STEEL COMPONENTS; SUPERVISED CLASSIFICATION; WORKING FLUID;

ARTIFICIAL INTELLIGENCE; BAYESIAN NETWORKS; OPTIMIZATION;

SURFACE ROUGHNESS;

EID: 84870927834     PISSN: 09565515     EISSN: 15728145     Source Type: Journal    
DOI: 10.1007/s10845-011-0506-8     Document Type: Article

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