Prediction of Surface Roughness in Drilling of Polymers Using a Geometrical Model and Artificial Neural Networks

被引:5
|
作者
Baroiu, Nicusor [1 ]
Costin, Georgiana-Alexandra [1 ]
Teodor, Virgil Gabriel [1 ]
Nedelcu, Dumitru [2 ]
Tabacaru, Valentin [1 ]
机构
[1] Dunarea de Jos Univ Galati, Fac Engn, Dept Mfg Engn, 111 Domneasca Str, Galati 800201, Romania
[2] Gheorghe Asachi Tech Univ Iasi, Fac Machine Mfg & Ind Management, 43 Prof Dr Doc Dimitrie Mangeron, Iasi 700050, Romania
关键词
roughness; helical drill; polymeric materials; artificial neural network (ANN); CUTTING PARAMETERS; HOLE QUALITY; MACHINABILITY; DELAMINATION;
D O I
10.37358/MP.20.3.5390
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Polymeric materials are synthetic macromolecular products, of which, by mechanical or thermal processing, objects of various shapes can be obtained, with wide uses in industry and commerce. This paper deals with the roughness of surfaces obtained during drilling of three polymeric materials: polyamide - PA6, polyacetal - POM-C and high density polyamide - HDPE 1000. In the experimental research was used a EAICO MILL 55 milling machine numerical controlled and HS steel helical drills with two straight cutting edges with the diameter of emptyset8 mm and emptyset10 mm, respectively. Experimental determinations consisted in drilling of the polymeric materials by modifying some parameters of the cutting regime, and determining the roughness of the surface of the holes machined, using the Mitutoyo Surftest SJ-210 rough meter. The purpose of the paper is to predict the roughness of the machined surfaces as one of the important surface quality indicators by using a geometrical model and an artificial neural network (ANN) methodology.
引用
收藏
页码:160 / 173
页数:14
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