Multi-objective optimization of surface roughness, recast layer thickness and surface crack density in WEDM of Al2124/SiCp using desirability approach

被引:11
|
作者
Reddy, B. Sridhar [1 ]
Rao, A. B. Koteswara [1 ]
Janardhana, G. Ranga [2 ]
机构
[1] Gayatri Vidya Parishad Coll Engn Autonomous, Mech Engn Dept, Visakhapatnam 530048, Andhra Pradesh, India
[2] JNTUA Univ Coll Engn, Mech Engn Dept, Anantapur 515002, Andhra Pradesh, India
关键词
Central composite design (CCD); Surface roughness (SR); Recast layer thickness (RCT); Surface crack density (SCD); Desirability approach;
D O I
10.1016/j.matpr.2020.04.563
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Engineered materials like Aluminum Metal Matrix Composites (ALMMCs) have tailor-made properties like high specific strength, low coefficient of thermal expansion (CTE), high thermal and electrical conductivity along with improved tribological properties. ALMMCs suitable for making the components used in automobile, and aerospace industry to enhance engine performance. In this paper, custom-made composite material Al2124/SiCP is machined by Wire cut Electric Discharge Machine (WEDM). The machining factors are pulse on time (T-on), pulse off time (T(of)f), current (IP), and servo voltage (SV) designed as per Central Composite Design (CCD). The response parameters, namely, Surface Roughness (SR), Recast Layer Thickness (RCT), and Surface Crack Density (SCD) are optimized by multi-objective optimization through desirability to improve the fatigue life of the component by selecting optimum input parameters. ANOVA results indicate that SR is influenced by T-on, SV, IP*SV, and T-on*T-on. RCT is influenced by T-on, T-off, IP, and T-on*SV. On the other hand, SCD is influenced by IP, IP*SV. The average values of SR, RCT, and SCD ranges between 1.369 and 3.325 mu m, 3.926-64.083 mu m, and 0.0449-0.1082 mu m/mm(2), respectively, for the range of input parameters. The confirmation experiments conducted at optimum design parameters (T-on = 119.056 mu s, T-off = 47.082 mu s, IP = 20 A, SV = 50 V) obtained through the desirability approach are found in reasonable agreement with the experimental results. (C) 2020 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1320 / 1326
页数:7
相关论文
共 50 条
  • [21] Evaluation and multi-objective optimization of nose wear, surface roughness and cutting forces using grey relation analysis (GRA)
    Sonawane, Gaurav D.
    Sargade, Vikas G.
    JOURNAL OF THE BRAZILIAN SOCIETY OF MECHANICAL SCIENCES AND ENGINEERING, 2019, 41 (12)
  • [22] Investigation of cutting temperature, cutting force and surface roughness using multi-objective optimization for turning of Ti-6Al-4 V (ELI)
    Shah, Darshit R.
    Pancholi, Nilesh
    Gajera, Hiren
    Patel, Bhavesh
    MATERIALS TODAY-PROCEEDINGS, 2022, 50 : 1379 - 1388
  • [23] Modelling Dimensional Accuracy and Surface Roughness in Resin Additive Manufacturing through Neural Network: A Multi-objective Optimization Approach in Dentistry
    Sharma, Anmol
    Bharti, Pushpendra S.
    JOURNAL OF MATERIALS ENGINEERING AND PERFORMANCE, 2025,
  • [24] Multi-objective Optimization and Predictive Modeling of Surface roughness and Material removal rate in Turning using Grey relational and Regression Analysis
    Sahoo, Ashok Kumar
    Baral, Achyuta Nanda
    Rout, Arun Kumar
    Routra, B. C.
    INTERNATIONAL CONFERENCE ON MODELLING OPTIMIZATION AND COMPUTING, 2012, 38 : 1606 - 1627
  • [25] Fabrication and multi-objective optimization of friction stir processed aluminium based surface composites using Taguchi approach
    Butola, Ravi
    Chandra, Prakash
    Bector, Kartikeya
    Singari, Ranganath M.
    SURFACE TOPOGRAPHY-METROLOGY AND PROPERTIES, 2021, 9 (02)
  • [26] Predictive modeling and multi objective optimization of Al 6063 for engraving depth and surface roughness using grey relational and regression analysis
    Pritam A.
    Dash R.R.
    Mallik R.K.
    Materials Today: Proceedings, 2023, 80 : 3464 - 3470
  • [27] Multi-objective optimization of surface roughness, thrust force, and torque produced by novel drill geometries using Taguchi-based GRA
    Güven Meral
    Murat Sarıkaya
    Mozammel Mia
    Hakan Dilipak
    Ulvi Şeker
    Munish K. Gupta
    The International Journal of Advanced Manufacturing Technology, 2019, 101 : 1595 - 1610
  • [28] Multi-objective optimization of surface roughness, thrust force, and torque produced by novel drill geometries using Taguchi-based GRA
    Meral, Guven
    Sarikaya, Murat
    Mia, Mozammel
    Dilipak, Hakan
    Seker, Ulvi
    Gupta, Munish K.
    INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2019, 101 (5-8): : 1595 - 1610
  • [29] Multi-objective optimization of turning process parameters and wood sawdust contents using response surface methodology for the minimized surface roughness of recycled plastic/wood sawdust composites
    Srivabut, Chainarong
    Rawangwong, Surasit
    Hiziroglu, Salim
    Homkhiew, Chatree
    COMPOSITES PART C: OPEN ACCESS, 2024, 14
  • [30] Multi-objective optimization to enhance surface integrity in WEDM for Al-matrix composite: A comparative assessment of self-weight adjusting MCDMs and objective weight integrated hybrid TOPSIS methods
    Anand, Gaurav
    Sardar, Santanu
    Sah, Satesh
    Guha, Ashim
    Das, Debdulal
    RESULTS IN SURFACES AND INTERFACES, 2025, 18