Investigation and modelling of process parameters and workpiece dimensions influence on material removal rate in CWEDT process

被引:14
作者
Gjeldum, Nikola [1 ]
Bilic, Bozenko [1 ]
Veza, Ivica [1 ]
机构
[1] Univ Split, Fac Elect Engn Mech Engn & Naval Architecture, Split, Croatia
关键词
neural networks; cylindrical parts; hard machinable material; material removal rate (MRR); cylindrical wire electrical discharge turning (CWEDT); DISCHARGE MACHINING PROCESS; SURFACE-ROUGHNESS; NEURAL-NETWORK; TURNING CWEDT; OPTIMIZATION; PERFORMANCE; PREDICTION; EDM;
D O I
10.1080/0951192X.2014.900868
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Cylindrical wire electrical discharge turning (CWEDT) is a special form of wire electrical discharge machining (WEDM) process, which uses submerged rotation spindle as a clamping device for workpiece rotation in order to produce cylindrical parts. This study aims at determining influence on material removal rate (MRR) of CWEDT as an objective function. In the preliminary experiments, the widely used X5CrNi18-10 (DIN) and hard machinable S390PM (DIN) were used. The results of preliminary experiments showed that the type of steel is not the factor that has a significant influence on MRR. Pulse maximum current, pulse pause time, rotation speed, length of discharge area and cutting radius were used in MRR mathematical modelling by neural network programming. The results of the study exhibit that among the machining parameters, the pulse maximum current has the strongest influence on MRR. When the pulse maximum current increases, MRR increases as well. The discharge area length has an influence on MRR only on higher pulse maximum current values, and by the increase of the discharge area length, the MRR also increases. The derived mathematical model for MRR, which was finally validated and tested, enables calculation of complex cylindrical part production machining time for the given experimental set-up condition.
引用
收藏
页码:715 / 728
页数:14
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