Determination of optimum amount lubricant in drilling using soft-computing tools: Desired surface roughness

被引:0
|
作者
Nandi A.K. [1 ]
Davim J.P. [2 ]
机构
[1] Department of General Engineering Design, Central Mechanical Engineering Research Institute, WB, Durgapur 713209, MG Avenue
[2] Department of Mechanical Engineering, University of Aveiro, Campus Santiago
关键词
Drilling; FLC; Fuzzy Logic Controller; GA; Genetic Algorithm; Optimum amount of lubricant; Surface roughness;
D O I
10.1504/ijmpt.2010.029462
中图分类号
学科分类号
摘要
Here, an approach based on soft-computing tools is proposed to control the optimum amount of lubricant required in drilling to achieve a desired surface roughness. Two Fuzzy Logic Controllers (FLCs), using TSK-type and Mamdani-type fuzzy rules are developed which are later adopted to optimise the lubricant rate using Genetic Algorithm (GA). A comparison of optimisation results based on FLCs with experimental values shows that FLC with TSK-type fuzzy rule is more efficient for real implementation. Copyright © 2010 Inderscience Enterprises Ltd.
引用
收藏
页码:102 / 116
页数:14
相关论文
共 23 条
  • [1] Determination of optimum amount lubricant in drilling using soft-computing tools: desired surface roughness
    Nandi, Arup Kumar
    Davim, J. Paulo
    INTERNATIONAL JOURNAL OF MATERIALS & PRODUCT TECHNOLOGY, 2010, 37 (1-2): : 102 - 116
  • [2] Surface roughness prediction in machining using soft computing
    Samanta, B.
    INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING, 2009, 22 (03) : 257 - 266
  • [3] Prediction of workpiece surface roughness using soft computing
    Samanta, B.
    Erevelles, W.
    Omurtag, Y.
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE, 2008, 222 (10) : 1221 - 1232
  • [4] DETECTION OF QRS COMPLEX OF FETAL ECG USING BIOLOGICALLY INSPIRED SOFT-COMPUTING TOOLS
    Anoop, Saladi. S. V. K. K.
    Prabhu, Ch. Midhun
    Penumala, Sunil Kumar
    2009 ANNUAL IEEE INDIA CONFERENCE (INDICON 2009), 2009, : 147 - 150
  • [5] Predicting the crack repair rate of self-healing concrete using soft-computing tools
    Lou, Yuanfeng
    Wang, Huiling
    Nasir Amin, Muhammad
    Ul Arifeen, Siyab
    Dodo, Yakubu
    Althoey, Fadi
    Deifalla, Ahmed Farouk
    MATERIALS TODAY COMMUNICATIONS, 2024, 38
  • [6] A soft computing system using intelligent imputation strategies for roughness prediction in deep drilling
    Maciej Grzenda
    Andres Bustillo
    Pawel Zawistowski
    Journal of Intelligent Manufacturing, 2012, 23 : 1733 - 1743
  • [7] A soft computing system using intelligent imputation strategies for roughness prediction in deep drilling
    Grzenda, Maciej
    Bustillo, Andres
    Zawistowski, Pawel
    JOURNAL OF INTELLIGENT MANUFACTURING, 2012, 23 (05) : 1733 - 1743
  • [8] Using Soft Computing Methods as an Effective Tool in Predicting Surface Roughness
    Al Hazza, Muataz Hazza F.
    Adesta, Erry Y. T.
    Seder, Amin M. F.
    2015 4TH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTER SCIENCE APPLICATIONS AND TECHNOLOGIES (ACSAT), 2015, : 9 - 13
  • [9] Computer vision measurement and optimization of surface roughness using soft computing approaches
    Beemaraj, Radha Krishnan
    Sekar, Mathalai Sundaram Chandra
    Vijayan, Venkatraman
    TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL, 2020, 42 (13) : 2475 - 2481
  • [10] OPTIMAL MQL AND CUTTING CONDITIONS DETERMINATION FOR DESIRED SURFACE ROUGHNESS IN TURNING OF BRASS USING GENETIC ALGORITHMS
    Gaitonde, V. N.
    Karnik, S. R.
    Paulo Davim, J.
    MACHINING SCIENCE AND TECHNOLOGY, 2012, 16 (02) : 304 - 320