Mathematical modeling of process parameters on hard turning of AIST 316 SS by WC insert

被引:0
|
作者
Ranganathan, S. [1 ]
Senthilvelan, T. [2 ]
Sriram, G. [1 ]
机构
[1] Sri Chandrasekharendra Saraswathi Vishwa Maha Vid, Dept Mech Engn, Enathur 631561, Kanchipuram, India
[2] Pondicherry Engn Coll, Dept Mech Engn, Pondicherry 605104, India
来源
JOURNAL OF SCIENTIFIC & INDUSTRIAL RESEARCH | 2009年 / 68卷 / 07期
关键词
ANOVA; Factorial design; Hard turning; Predictive model; Surface roughness; Tool wear; FINISH;
D O I
暂无
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This paper presents a newly developed mathematical modeling for process 0 parameters on hard turning of AISI 316 stainless steel by tungsten carbide inserts (WC). Regression analysis and ANOVA theory was used to predict surface roughness (Ra) and tool wear (V-B). WC tool inserts performed machining of AISI 316 SS to study main and interaction effects of process parameters [cutting speed (Vs), feed rate (fs) and depth of cut (a(p))]. Adequacies of developed model were verified by calculation of correlation coefficient (r). These models can be effectively used to predict Ra of work piece and V-B Of WC insert.
引用
收藏
页码:592 / 596
页数:5
相关论文
共 50 条
  • [41] Experimental analysis and optimization of abrasive waterjet deep hole drilling process parameters for SS AISI 316L
    Chandar, Bharani
    Lenin, N.
    Kumar, Siva
    Gupta, Naveen Kumar
    Karthick, Alagar
    Suriyan, Rathina
    Panchal, Hitesh
    Kumar, Abhinav
    Patel, Anand
    Sadasivuni, Kishor Kumar
    JOURNAL OF MATERIALS RESEARCH AND TECHNOLOGY-JMR&T, 2023, 26 : 7984 - 7997
  • [42] Predicting the Effects of Cutting Parameters and Tool Geometry on Hard Turning Process Using Finite Element Method
    Zhang, Xueping
    Wu, Shenfeng
    Wang, Heping
    Liu, C. Richard
    JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME, 2011, 133 (04):
  • [43] Effects of Process Parameters on White Layer Formation and Morphology in Hard Turning of AISI52100 Steel
    Zhang, Xiao-Ming
    Chen, Li
    Ding, Han
    JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME, 2016, 138 (07):
  • [44] Multi-objective optimization of turning parameters for targeting surface roughness and maximizing material removal rate in dry turning of AISI 316L with PVD-coated cermet insert
    Touggui, Youssef
    Belhadi, Salim
    Mechraoui, Salah-Eddine
    Uysal, Alper
    Yallese, Mohammed Athmane
    Temmar, Mustapha
    SN APPLIED SCIENCES, 2020, 2 (08):
  • [45] Multi-objective optimization of turning parameters for targeting surface roughness and maximizing material removal rate in dry turning of AISI 316L with PVD-coated cermet insert
    Youssef Touggui
    Salim Belhadi
    Salah-Eddine Mechraoui
    Alper Uysal
    Mohammed Athmane Yallese
    Mustapha Temmar
    SN Applied Sciences, 2020, 2
  • [46] Statistical analysis, modeling and multi-objective optimization of parameters intermittent turning process of AISI D3
    Khelfaoui, F.
    Yallese, M. A.
    Ouelaa, N.
    Chihaoui, S.
    Belhadi, S.
    JOURNAL OF MECHANICAL ENGINEERING AND SCIENCES, 2023, 17 (02) : 9492 - 9506
  • [47] Modeling and optimization of turning process parameters during the cutting of polymer (POM C) based on RSM, ANN, and DF methods
    Chabbi, A.
    Yallese, M. A.
    Nouioua, M.
    Meddour, I.
    Mabrouki, T.
    Girardin, Francois
    INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2017, 91 (5-8) : 2267 - 2290
  • [48] Mathematical and Prediction Modeling of Material Removal Rate for Evaluating the Effects of Process Parameters
    Kushwah, Sourabh Singh
    Kasdekar, Dinesh Kumar
    Agrawal, Sharad
    AMBIENT COMMUNICATIONS AND COMPUTER SYSTEMS, RACCCS 2017, 2018, 696 : 509 - 523
  • [49] Effect of Cutting Parameters on Sustainable Machining Performance of Coated Carbide Tool in Dry Turning Process of Stainless Steel 316
    Bagaber, Salem A.
    Yusoff, Ahmed Razlan
    GREEN AND SUSTAINABLE TECHNOLOGY, 2017, 1828
  • [50] Modeling and optimization of turning process parameters during the cutting of polymer (POM C) based on RSM, ANN, and DF methods
    A. Chabbi
    M.A. Yallese
    M. Nouioua
    I. Meddour
    T. Mabrouki
    François Girardin
    The International Journal of Advanced Manufacturing Technology, 2017, 91 : 2267 - 2290