Design of grinding factors based on response surface methodology

被引:55
作者
Krajnik, P [1 ]
Kopac, J [1 ]
Sluga, A [1 ]
机构
[1] Univ Ljubljana, Fac Mech Engn, SI-1000 Ljubljana, Slovenia
关键词
grinding; surface roughness; response surface methodology; modelling; optimization; regression;
D O I
10.1016/j.jmatprotec.2005.02.187
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The presented paper describes a systematic methodology for empirical modelling and optimization of the plunge centreless grinding process. The assessment of microgeometric quality defining quantity is supported by post-process surface roughness measurements. The design of grinding factors is based on response surface methodology, which integrates a design of experiment, regression modelling technique for fitting a model to experimental data and basic optimization. Central composite response surface design has been ernployed to develop a second-order surface roughness model. The model has been fully constructed by determination of its structure and regression coefficients. The final goal of experimental study focuses on determination of optimum centreless grinding system set-up and operating conditions for minimization of surface roughness. The computer-aided single-objective optimization, solved by non-linear programming and genetic algorithm, is applied. The results of two different optimization approaches for determination of optimal operating conditions are compared. Finally, further research directions are presented. (c) 2005 Elsevier B.V. All rights reserved.
引用
收藏
页码:629 / 636
页数:8
相关论文
共 11 条
  • [1] [Anonymous], 2017, DESIGN ANAL EXPT
  • [2] DONGARRA JJ, 1979, LINPACK USERS GUIDE
  • [3] Evolutionary computing
    Eiben, AE
    Schoenauer, M
    [J]. INFORMATION PROCESSING LETTERS, 2002, 82 (01) : 1 - 6
  • [4] Roughness parameters
    Gadelmawla, ES
    Koura, MM
    Maksoud, TMA
    Elewa, IM
    Soliman, HH
    [J]. JOURNAL OF MATERIALS PROCESSING TECHNOLOGY, 2002, 123 (01) : 133 - 145
  • [5] Adequacy of matrix experiment in grinding
    Krajnik, P
    Kopac, J
    [J]. JOURNAL OF MATERIALS PROCESSING TECHNOLOGY, 2004, 157 : 566 - 572
  • [6] Maros I., 2003, COMPUTATIONAL TECHNI
  • [7] MYERS H, 2002, PROCESS PRODUCT OPTI
  • [8] Press W. H., 1989, NUMERICAL RECIPES PA
  • [9] A multi-objective genetic algorithm (GA) approach for optimization of surface grinding operations
    Saravanan, R
    Asokan, P
    Sachidanandam, M
    [J]. INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE, 2002, 42 (12) : 1327 - 1334
  • [10] Spall J. C., 2003, INTRO STOCHASTIC SEA, DOI [10.1002/0471722138, DOI 10.1002/0471722138]