Optimization of WEDM Parameters While Machining Biomedical Materials Using EDAS-PSO

被引:6
作者
Sharma, Vishal S. [1 ,2 ]
Sharma, Neeraj [3 ]
Singh, Gurraj [1 ]
Gupta, Munish Kumar [4 ]
Singh, Gurminder [5 ]
机构
[1] Dr BR Ambedkar Natl Inst Technol, Dept Ind & Prod Engn, Jalandhar 144027, India
[2] Univ Witwatersrand, Sch Mech Ind & Aeronaut Engn, ZA-2000 Johannesburg, South Africa
[3] Maharishi Markandeshwar, Mech Engn Dept, Ambala 134003, India
[4] Opole Univ Technol, Fac Mech Engn, 76 Proszkowska St, PL-45758 Opole, Poland
[5] Indian Inst Technol, Dept Mech Engn, Mumbai 400076, India
关键词
EDAS-PSO; optimization; pure titanium (Grade 2); WEDM; TITANIUM GRADE 6; MULTIOBJECTIVE OPTIMIZATION; SURFACE INTEGRITY; ALLOY; EDM; PERFORMANCE;
D O I
10.3390/ma16010114
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
In the present work, an attempt has been made to study the influence of process parameters of the wire electric discharge machining (WEDM) process on the machining characteristics. The commercially pure titanium is machined by WEDM using brass wire as an electrode. The input parameters in this work were pulse on-time (A(on)), pulse off-time (A(off)), servo voltage (SV) and wire tension (WT). On the other hand, dimensional accuracy (DA), average surface roughness (R-a) and maximum surface roughness (R-z) were chosen as the response parameters. The empirical relations developed for response characteristics were solved collectively using Evaluation Based on Distance from Average Solution (EDAS) and Particle Swarm Optimization (PSO). The optimized setting for minimizing the surface irregularities while machining titanium alloy on WEDM is predicted as A(on): 8 mu s; A(off): 13 mu s; SV: 45 V; and WT: 8 N. Moreover, the predicted solution at the optimized parametric settings came out as DA: 95%; Ra: 3.163 mu m; Rz: 22.99 mu m; WL: 0.0182 g; and DR: 0.1277 mm. The validation experiments at the optimized setting showed the close agreement between predicted and experimental values. The morphological study by scanning electron microscopy (SEM) at the optimized setting revealed a significant reduction in surface defects such as micro cracks, micro cavities, globules and sub-surfaces, etc. In a nutshell, the study justified the effectiveness of EDAS-PSO in efficiently predicting the results for machining of pure titanium (Grade 2) using the WEDM process.
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页数:26
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共 42 条
  • [1] A review on current research trends in electrical discharge machining (EDM)
    Abbas, Norliana Mohd
    Solomon, Darius G.
    Bahari, Md. Fuad
    [J]. INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE, 2007, 47 (7-8) : 1214 - 1228
  • [2] INFLUENCE OF MACHINE FEED RATE IN WEDM OF TITANIUM Ti-6Al-4V WITH CONSTANT CURRENT (6A) USING BRASS WIRE
    Alias, Aniza
    Abdullah, Bulan
    Abbas, Norliana Mohd
    [J]. INTERNATIONAL SYMPOSIUM ON ROBOTICS AND INTELLIGENT SENSORS 2012 (IRIS 2012), 2012, 41 : 1806 - 1811
  • [3] Multi-response Optimization of WEDM Parameters Using an Integrated Approach of RSM–GRA Analysis for Pure Titanium
    Chaudhari R.
    Vora J.
    Parikh D.M.
    Wankhede V.
    Khanna S.
    [J]. Vora, Jay (vorajaykumar@gmail.com), 1600, Springer (101): : 117 - 126
  • [4] Biomedical applications of titanium and its alloys
    Elias, C. N.
    Lima, J. H. C.
    Valiev, R.
    Meyers, M. A.
    [J]. JOM, 2008, 60 (03) : 46 - 49
  • [5] Curved profiles machining of Ti6Al4V alloy through WEDM: investigations on geometrical errors
    Farooq, Muhammad Umar
    Ali, Muhammad Asad
    He, Yong
    Khan, Aqib Mashood
    Pruncu, Catalin Iulin
    Kashif, Muhammad
    Ahmed, Naveed
    Asif, Noman
    [J]. JOURNAL OF MATERIALS RESEARCH AND TECHNOLOGY-JMR&T, 2020, 9 (06): : 16186 - 16201
  • [6] Integration of Fuzzy AHP and Fuzzy TOPSIS Methods for Wire Electric Discharge Machining of Titanium (Ti6Al4V) Alloy Using RSM
    Fuse, Kishan
    Dalsaniya, Arrown
    Modi, Dhananj
    Vora, Jay
    Pimenov, Danil Yurievich
    Giasin, Khaled
    Prajapati, Parth
    Chaudhari, Rakesh
    Wojciechowski, Szymon
    [J]. MATERIALS, 2021, 14 (23)
  • [7] Modelling and multi-objective optimization of process parameters of wire electrical discharge machining using non-dominated sorting genetic algorithm-II
    Garg, Mohinder P.
    Jain, Ajai
    Bhushan, Gian
    [J]. PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE, 2012, 226 (A12) : 1986 - 2001
  • [8] An adaptive neuro-fuzzy and NSGA-II-based hybrid approach for modelling and multi-objective optimization of WEDM quality characteristics during machining titanium alloy
    Goyal, Ashish
    Gautam, Nipun
    Pathak, Vimal Kumar
    [J]. NEURAL COMPUTING & APPLICATIONS, 2021, 33 (23) : 16659 - 16674
  • [9] A Soft Computing-Based Analysis of Cutting Rate and Recast Layer Thickness for AZ31 Alloy on WEDM Using RSM-MOPSO
    Goyal, Kapil K.
    Sharma, Neeraj
    Dev Gupta, Rahul
    Singh, Gurpreet
    Rani, Deepika
    Banga, Harish Kumar
    Kumar, Raman
    Pimenov, Danil Yurievich
    Giasin, Khaled
    [J]. MATERIALS, 2022, 15 (02)
  • [10] Revealing the WEDM Process Parameters for the Machining of Pure and Heat-Treated Titanium (Ti-6Al-4V) Alloy
    Gupta, Nitin Kumar
    Somani, Nalin
    Prakash, Chander
    Singh, Ranjit
    Walia, Arminder Singh
    Singh, Sunpreet
    Pruncu, Catalin Iulian
    [J]. MATERIALS, 2021, 14 (09)