Optimization of machining parameters in sinking electrical discharge machine of caldie plastic mold tool steel

被引:0
|
作者
Ali Kalyon
机构
[1] Karabuk University,Department of Manufacturing Engineering, Faculty of Technology
来源
Sādhanā | 2020年 / 45卷
关键词
EDM; graphite; copper; caldie; Taguchi; ANOVA;
D O I
暂无
中图分类号
学科分类号
摘要
The aim of this study was to investigate the machinability of caldie cold work tool steel using the electro erosion technique. In the experimental study, graphite and copper were used as the electrode materials. Three levels for discharge current (6, 12 and 25 A) and three levels for pulse duration (50, 100 and 200 µs) were used as machining parameters. The experimental model was designed according to the Taguchi L18 orthogonal array. Signal/noise ratios, graphs and regression analysis were used to evaluate the results of the experiments. Using the Taguchi technique, the optimum machining parameters were determined with process outputs for surface roughness, material removal rate and electrode wear rate. The optimum levels were found to be A1B1C1 for surface roughness and electrode wear rate and A2B3C3 for material removal rate. The effect of control factors on experimental outputs was calculated by performing ANOVA. According to the ANOVA results, discharge current was the most effective parameter on machinability. When the experimental data were compared statistically with the Taguchi optimization and regression model data, the results of the designed models were shown to be successful.
引用
收藏
相关论文
共 50 条
  • [1] Optimization of machining parameters in sinking electrical discharge machine of caldie plastic mold tool steel
    Kalyon, Ali
    SADHANA-ACADEMY PROCEEDINGS IN ENGINEERING SCIENCES, 2020, 45 (01):
  • [2] Optimization of Machining Parameters of Electrical Discharge Machining Tool Steel 1.2713
    Swiercz, Rafal
    Oniszczuk-Swiercz, Dorota
    Dabrowski, Lucjan
    Zawora, Jozef
    XIII INTERNATIONAL CONFERENCE ELECTROMACHINING 2018, 2018, 2017
  • [3] Optimization of Machining Parameters in Electrical Discharge Machining (EDM) of 304 Stainless Steel
    Rajmohan, T.
    Prabhu, R.
    Rao, Subba G.
    Palanikumar, K.
    INTERNATIONAL CONFERENCE ON MODELLING OPTIMIZATION AND COMPUTING, 2012, 38 : 1030 - 1036
  • [4] Micro electrical discharge machining for tool and mold making
    Gruber, Hanspeter
    Wolf, André
    ZWF Zeitschrift fuer Wirtschaftlichen Fabrikbetrieb, 2000, 95 (06): : 26 - 28
  • [5] Examination and Optimization of Machining Parameters in Electrical Discharge Machining of UNS T30407 Steel
    Singh, Palwinder
    Singh, Lakhvir
    JOURNAL OF ADVANCED MANUFACTURING SYSTEMS, 2022, 21 (03) : 573 - 589
  • [6] Machine Learning-Driven Approach for Reducing Tool Wear in Die-Sinking Electrical Discharge Machining
    Cogun, Can
    Ayli, Ece
    ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING, 2025,
  • [7] Machining Performance Analysis in Electrical Discharge Machining of Alloy Tool Steel
    Singh, Palwinder
    Singh, Amandeep
    Singh, Lakhvir
    SAE INTERNATIONAL JOURNAL OF MATERIALS AND MANUFACTURING, 2023, 16 (01) : 83 - 95
  • [8] Machining Performance Analysis in Electrical Discharge Machining of Alloy Tool Steel
    Singh, Palwinder
    Singh, Amandeep
    Singh, Lakhvir
    SAE International Journal of Materials and Manufacturing, 2022, 16 (01)
  • [9] Suspended SiC particle deposition on plastic mold steel surfaces in powder-mixed electrical discharge machining
    Ekmekci, Bulent
    Ulusoz, Fevzi
    Ekmekci, Nihal
    Yasar, Hamidullah
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE, 2015, 229 (03) : 475 - 486
  • [10] Optimization of electrical discharge machining parameters on hardened die steel using Firefly Algorithm
    S. Bharathi Raja
    C. V. Srinivas Pramod
    K. Vamshee Krishna
    Arvind Ragunathan
    Somalaraju Vinesh
    Engineering with Computers, 2015, 31 : 1 - 9