Optimization of process parameters for friction weld steel tube to forging joints

被引:25
作者
Balta, Berna [1 ]
Arici, A. Armagan [1 ]
Yilmaz, Muharrem [2 ]
机构
[1] Kocaeli Univ, Dept Mech Engn, TR-41380 Kocaeli, Umuttepe, Turkey
[2] Kocaeli Univ, Dept Mechatron Engn, TR-41380 Kocaeli, Umuttepe, Turkey
关键词
Friction welding; Steel tube to forging joints; Tensile strength; Elongation; Petal test; Petal crack length; DUPLEX STAINLESS-STEEL; RESPONSE-SURFACE METHODOLOGY; CARBON-STEEL; MILD-STEEL; MULTIOBJECTIVE OPTIMIZATION; TENSILE-STRENGTH; MICROSTRUCTURE; PREDICTION; ALLOY;
D O I
10.1016/j.matdes.2016.04.072
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In this study, structural durability of continuous drive friction welding (CDFW) of steel tube/forging joints is inspected. The relationship between the welding parameters and the mechanical properties is developed by using response surfacemethodology (RSM). While keeping rotation speed constant, friction pressure, friction time, forging pressure and forging time are used as input variables, and the tensile strength, elongation (%) and petal crack length are selected as output variables. For setting optimum condition parameters, the desirability function is used. According to the confirmation experiment, the difference between the values of tensile strength, elongation (%) and petal crack length, predicted by response surface curve and the experimental data for the maximum desirability is 1.06%, 13.37% and 2.44%, respectively. Furthermore, the predicted model looks reasonably accurate based on the analysis of variance (ANOVA). Using the response curve, one may estimate the tensile strength, elongation (%) and petal crack length for similar joints. In comparison to previous studies, optimization of CDFW parameters for forging bracket to steel tube joints is investigated for the first time. Petal test for the optimization of friction welding is also utilized for the first time. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:209 / 222
页数:14
相关论文
共 36 条
[1]   Multi-objective Optimization of Continuous Drive Friction Welding Process Parameters Using Response Surface Methodology with Intelligent Optimization Algorithm [J].
Ajith, P. M. ;
Husain, T. M. Afsal ;
Sathiya, P. ;
Aravindan, S. .
JOURNAL OF IRON AND STEEL RESEARCH INTERNATIONAL, 2015, 22 (10) :954-960
[2]   Multiobjective optimization of friction welding of UNS S32205 duplex stainless steel [J].
Ajith, P. M. ;
Barik, Birendra Kumar ;
Sathiya, P. ;
Aravindan, S. .
DEFENCE TECHNOLOGY, 2015, 11 (02) :157-165
[3]   An investigation into reutilizing of waste materials using friction welding and upset manufacturing methods [J].
Akata, H. Erol ;
Sahin, Mumin ;
Ipekci, M. Turan .
INDUSTRIAL LUBRICATION AND TRIBOLOGY, 2007, 59 (05) :230-235
[4]   Artificial neural network modeling studies to predict the friction welding process parameters of Incoloy 800H joints [J].
Anand, K. ;
Barik, Birendra Kumar ;
Tamilmannan, K. ;
Sathiya, P. .
ENGINEERING SCIENCE AND TECHNOLOGY-AN INTERNATIONAL JOURNAL-JESTECH, 2015, 18 (03) :394-407
[5]   The impact of heat input on the strength, toughness, microhardness, microstructure and corrosion aspects of friction welded duplex stainless steel joints [J].
Asif, Mohammed M. ;
Shrikrishna, Kulkarni Anup ;
Sathiya, P. ;
Goel, Sunkulp .
JOURNAL OF MANUFACTURING PROCESSES, 2015, 18 :92-106
[6]  
Balta B, ASME MSEC2014
[7]   Optimizing the laser-welded butt joints of medium carbon steel using RSM [J].
Benyounis, KY ;
Olabi, AG ;
Hashmi, MSJ .
JOURNAL OF MATERIALS PROCESSING TECHNOLOGY, 2005, 164 :986-989
[8]   FRICTIONAL BEHAVIOR OF MILD-STEEL IN FRICTION WELDING [J].
DUFFIN, FD ;
BAHRANI, AS .
WEAR, 1973, 26 (01) :53-74
[9]   ON A MODEL FOR FRICTIONING STAGE IN FRICTION WELDING OF THIN TUBES [J].
FRANCIS, A ;
CRAINE, RE .
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER, 1985, 28 (09) :1747-1755
[10]  
Handa A., 2013, INT J ENG SCI RES TE, V2, P2818