Prediction of depth removal in leather surface grit blasting using neural networks and Box-Behnken design of experiments

被引：0
|
作者：
Hu, Zhongxu [1 ]
Bicker, Robert [1 ]
Marshall, Chris [1 ]
机构：
[1] Department of Mechanical and System Engineering, Newcastle University Upon Tyne, Dummy, NE1 7RU, United Kingdom
来源：
International Journal of Advanced Manufacturing Technology | 2007年 / 32卷 / 7-8期
关键词：
In this work; leather material is for the first time prepared by grit blasting process in order to improve peel strength when bonding. Peel tests show that it is the surface depth of removal rather than surface roughness that dominates the bonding performance. Therefore; measurement of surface removal is critical for surface preparation of using a grit blasting process. Indirect measurement of preparation performance is essential due to the hazardous conditions for conventional sensing equipment in the blasting chamber. A neural network modelling approach is proposed for the prediction of surface removal of leather materials; and the neural network model also characterizes the process; which is very useful for machine design and optimum control. The data used for the training of the artificial neural network is collected through screening experiments; which was efficiently planned using the Box-Behnken design method. © Springer-Verlag London Limited 2007;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Journal article (JA)
引用
收藏
页码：732 / 738
相关论文
共 50 条
  • [1] Prediction of depth removal in leather surface grit blasting using neural networks and Box-Behnken design of experiments
    Zhongxu Hu
    Robert Bicker
    Chris Marshall
    The International Journal of Advanced Manufacturing Technology, 2007, 32 : 732 - 738
  • [2] Prediction of depth removal in leather surface grit blasting using neural networks and Box-Behnken design of experiments
    Hu, Zhongxu
    Bicker, Robert
    Marshall, Chris
    INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2007, 32 (7-8): : 732 - 738
  • [3] Optimization of electrochemical ammonia removal using Box-Behnken design
    Li, Miao
    Feng, Chuanping
    Zhang, Zhenya
    Liu, Xiang
    Ma, Weifang
    Xue, Qiang
    Sugiura, Norio
    JOURNAL OF ELECTROANALYTICAL CHEMISTRY, 2011, 657 (1-2) : 66 - 73
  • [4] Optimization of corona discharge process using Box-Behnken design of experiments
    Das, Dipayan
    Thakur, Rashmi
    Pradhan, Arun Kumar
    JOURNAL OF ELECTROSTATICS, 2012, 70 (06) : 469 - 473
  • [5] Removal of reactive orange 16 with nZVI-activated carbon/Ni: optimization by Box-Behnken design and performance prediction using artificial neural networks
    Seyedi, Maryam Sadat
    Sohrabi, Mahmoud Reza
    Motiee, Fereshteh
    Mortazavinik, Saeid
    Pigment and Resin Technology, 2022, 51 (05): : 463 - 476
  • [6] Removal of reactive orange 16 with nZVI-activated carbon/Ni: optimization by Box-Behnken design and performance prediction using artificial neural networks
    Seyedi, Maryam Sadat
    Sohrabi, Mahmoud Reza
    Motiee, Fereshteh
    Mortazavinik, Saeid
    PIGMENT & RESIN TECHNOLOGY, 2022, 51 (05) : 463 - 476
  • [7] Prediction of adsorption parameters for hydrogen sulfide removal from synthetic wastewater using Box-Behnken design
    Alenezi, Hamoud
    Al-Qabandi, Osamah
    JOURNAL OF ENGINEERING RESEARCH, 2023, 11 (02):
  • [8] Use of Box-Behnken design of experiments for the adsorption of chromium using immobilized macroalgae
    Rangabhashiyam, S.
    Nandagopal, M. S. Giri
    Nakkeeran, E.
    Keerthi, R.
    Selvaraju, N.
    DESALINATION AND WATER TREATMENT, 2016, 57 (54) : 26101 - 26113
  • [9] Use of Box-Behnken design of experiments for the adsorption of verofix red using biopolymer
    G. Annadurai
    R. Y. Sheeja
    Bioprocess Engineering, 1998, 18 : 463 - 466
  • [10] Use of Box-Behnken design of experiments for the adsorption of verofix red using biopolymer
    Annadurai, G
    Sheeja, RY
    BIOPROCESS ENGINEERING, 1998, 18 (06) : 463 - 466
12345