메뉴 건너뛰기




Volumn 39, Issue 5, 2012, Pages 5982-5989

Application of Particle Swarm Optimization technique for achieving desired milled surface roughness in minimum machining time

Author keywords

Face milling; Machining parameters; Machining time; Particle Swarm Optimization; Surface roughness

Indexed keywords

CUTTING SPEED; DEPTH OF CUT; DIMENSIONAL ACCURACY; EXPERIMENTAL INVESTIGATIONS; FACE MILLING; MACHINING OPERATIONS; MACHINING PARAMETERS; MACHINING TIME; OPTIMAL MACHINING PARAMETERS; PARTICLE SWARM OPTIMIZATION TECHNIQUE; PHYSICAL CONSTRAINTS; SURFACE FINISHES; THEORETICAL APPROACH; TRIAL AND ERROR; WORK EXPERIENCE;

EID: 84855873944     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2011.11.110     Document Type: Article
Times cited : (108)

References (17)
  • 2
    • 58149173522 scopus 로고    scopus 로고
    • Surface roughness prediction using measured data and interpolation in layered manufacturing
    • D. Ahn, H. Kim, and S. Lee Surface roughness prediction using measured data and interpolation in layered manufacturing Journal of Materials Processing Technology 209 2009 664 671
    • (2009) Journal of Materials Processing Technology , vol.209 , pp. 664-671
    • Ahn, D.1    Kim, H.2    Lee, S.3
  • 3
    • 79151483285 scopus 로고    scopus 로고
    • Modelling and prediction of surface roughness in turning operations using Artificial Neural Network and multiple regression method
    • doi:10.1016/j.eswa.2010.11.041
    • Asilturk, I.; & Cunkas, M. (2010). Modelling and prediction of surface roughness in turning operations using Artificial Neural Network and multiple regression method. Expert Systems with Applications doi:10.1016/j.eswa.2010.11.041.
    • (2010) Expert Systems with Applications
    • Asilturk, I.1    Cunkas, M.2
  • 4
    • 0036815452 scopus 로고    scopus 로고
    • Prediction of surface roughness in CNC face milling using neural networks and Taguchi's design of experiments
    • P.G. Benardos, and G.C. Vosniakos Prediction of surface roughness in CNC face milling using neural networks and Taguchi's design of experiments Robotics and Computer-Integrated Manufacturing 18 2002 343 354
    • (2002) Robotics and Computer-Integrated Manufacturing , vol.18 , pp. 343-354
    • Benardos, P.G.1    Vosniakos, G.C.2
  • 5
    • 39949083945 scopus 로고    scopus 로고
    • Prediction of surface roughness profile for milled surfaces suing an Artificial Neural Network and fractional geometry approach
    • I.A. El-Sonbaty, U.A. Khashaba, A.I. Selmy, and A.I. Ali Prediction of surface roughness profile for milled surfaces suing an Artificial Neural Network and fractional geometry approach Journal of Materials Processing Technology 200 2008 271 278
    • (2008) Journal of Materials Processing Technology , vol.200 , pp. 271-278
    • El-Sonbaty, I.A.1    Khashaba, U.A.2    Selmy, A.I.3    Ali, A.I.4
  • 7
    • 33751429157 scopus 로고    scopus 로고
    • A fuzzy expert system for optimizing parameters and predicting performances measures in hard-milling process
    • A. Iqbal, N. He, L. Li, and N.U. Dar A fuzzy expert system for optimizing parameters and predicting performances measures in hard-milling process Expert Systems with Applications 32 2007 1020 1027
    • (2007) Expert Systems with Applications , vol.32 , pp. 1020-1027
    • Iqbal, A.1    He, N.2    Li, L.3    Dar, N.U.4
  • 8
    • 78549280471 scopus 로고    scopus 로고
    • Cutting parameters optimization for prediction time via computer experiments
    • A. Jeang cutting parameters optimization for prediction time via computer experiments Applied Mathematical Modelling 35 2011 1354 1362
    • (2011) Applied Mathematical Modelling , vol.35 , pp. 1354-1362
    • Jeang, A.1
  • 11
    • 0141959043 scopus 로고    scopus 로고
    • An adaptive-network based fuzzy interference system for predicting of work piece surface roughness in end milling
    • S.-P. Lo An adaptive-network based fuzzy interference system for predicting of work piece surface roughness in end milling Journal of Materials Processing Technology 142 2003 665 675
    • (2003) Journal of Materials Processing Technology , vol.142 , pp. 665-675
    • Lo, S.-P.1
  • 12
    • 0038003099 scopus 로고    scopus 로고
    • Surface roughness model for end milling: A semi-free cutting carbon case hardening steel (EN32) in dry condition
    • A. Mansour, and H. Abdalla Surface roughness model for end milling: a semi-free cutting carbon case hardening steel (EN32) in dry condition Journal of Materials Processing Technology 124 2002 183 191
    • (2002) Journal of Materials Processing Technology , vol.124 , pp. 183-191
    • Mansour, A.1    Abdalla, H.2
  • 13
    • 33750343161 scopus 로고    scopus 로고
    • Milling surface roughness prediction using evolutionary programing methods
    • C. Oguz, K. Cahit, and M. Cengiz Kayacan Milling surface roughness prediction using evolutionary programing methods Materials & Design 28 2007 657 666
    • (2007) Materials & Design , vol.28 , pp. 657-666
    • Oguz, C.1    Cahit, K.2    Cengiz Kayacan, M.3
  • 16
    • 71749087451 scopus 로고    scopus 로고
    • Prediction of surface roughness in the end milling machining using Artificial Neural Network
    • doi:10.1016/j.eswa.2009.07.033
    • Zain, A. M.; Haron, H.; Sharif, S. (2009b). Prediction of surface roughness in the end milling machining using Artificial Neural Network. Expert Systems with Applications doi:10.1016/j.eswa.2009.07.033.
    • (2009) Expert Systems with Applications
    • Zain, A.M.1    Haron, H.2    Sharif, S.3
  • 17
    • 77249143297 scopus 로고    scopus 로고
    • Application of GA to optimize cutting conditions for minimizing surface roughness in end milling machining process
    • A.M. Zain, H. Haron, and S. Sharif Application of GA to optimize cutting conditions for minimizing surface roughness in end milling machining process Expert Systems with Applications 37 2009 4650 4659
    • (2009) Expert Systems with Applications , vol.37 , pp. 4650-4659
    • Zain, A.M.1    Haron, H.2    Sharif, S.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.