399
Views
24
CrossRef citations to date
0
Altmetric
Articles

Prediction, monitoring and control of surface roughness in high-torque milling machine operations

, &
Pages 1129-1138 | Received 29 Jun 2011, Accepted 02 Mar 2012, Published online: 14 May 2012

References

  • Arizmendi , M. 2009 . Effect of tool setting error on the topography of surfaces machined by peripheral milling . International Journal of Machine Tools and Manufacture , 49 ( 1 ) : 36 – 52 .
  • Beggan , C. 1999 . Using acoustic emission to predict surface quality . International Journal of Advanced Manufacturing Technology , 15 ( 10 ) : 737 – 742 .
  • Benardos , P.G. and Vosniakos , G.C. 2002 . Prediction of surface roughness in CNC face milling using neural networks and Taguchi's design of experiments . Robotics and Computer-Integrated Manufacturing , 18 ( 5–6 ) : 343 – 354 .
  • Benardos , P.G. and Vosniakos , G.-C. 2003 . Predicting surface roughness in machining: a review . International Journal of Machine Tools and Manufacture , 43 ( 8 ) : 833 – 844 .
  • Brezocnik , M. and Kovacic , M. 2003 . Integrated genetic programming and genetic algorithm approach to predict surface roughness . Materials and Manufacturing Processes , 18 ( 3 ) : 475 – 491 .
  • Bustillo , A. 2011 . Avoiding neural network fine tuning by using ensemble learning: application to ball-end milling operations . The International Journal of Advanced Manufacturing Technology , 57 ( 5 ) : 521 – 532 .
  • Chen , J.C. and Lou , M.S. 2000 . Fuzzy-nets based approach to using an accelerometer for an in-process surface roughness prediction system in milling operations . International Journal of Computer Integrated Manufacturing , 13 ( 4 ) : 358 – 368 .
  • Choudhury , S.K. and Bartarya , G. 2003/2005 . Role of temperature and surface finish in predicting tool wear using neural network and design of experiments . International Journal of Machine Tools and Manufacture , 43 ( 7 ) : 747 – 753 .
  • Ciurana , J. , Quintana , G. and Garcia-Romeu , M.L. 2008 . Estimating the cost of vertical high-speed machining centres, a comparison between multiple regression analysis and the neural networks approach . International Journal of Production Economics , 115 ( 1 ) : 171 – 178 .
  • Correa , M. , Bielza , C. and Pamies-Teixeira , J. 2009 . Comparison of bayesian networks and artificial neural networks for quality detection in a machining process . Expert Systems with Applications , 36 ( 3 ) : 7270 – 7279 .
  • El-Mounayri , H. and Deng , H. 2010 . A generic and innovative approach for integrated simulation and optimisation of end milling using solid modelling and neural network . International Journal of Computer Integrated Manufacturing , 23 ( 1 ) : 40 – 60 .
  • Groover , M.P. and Society of Manufacturing Engineers . 2004 . Fundamentals of modern manufacturing: materials, processes, and systems , 2nd ed , New York : John Wiley & Sons .
  • Grzesik , W. 2008 . Influence of tool wear on surface roughness in hard turning using differently shaped ceramic tools . Wear , 265 ( 3–4 ) : 327 – 335 .
  • Ismail , F. 1993 . Generation of milled surfaces including tool dynamics and wear . Journal of Engineering for Industry , 115 ( 3 ) : 245 – 252 .
  • ISO-1302 . 1996 . Geometrical product specifications (GPS): rules and procedures for the assessment of surface texture. ISO-1302
  • Lee , H.S. 2006 . Systematic finishing of dies and moulds . International Journal of Machine Tools and Manufacture , 46 ( 9 ) : 1027 – 1034 .
  • López de Lacalle , L.N. and Lamikiz , A. 2008 . Machine tools for high performance machining , London : Springer .
  • Martellotti , M.E. 1941 . An analysis of the milling process . Transactions of ASME , 63 : 667
  • Montgomery , D. and Altintas , Y. 1991 . Mechanism of cutting force and surface generation in dynamic milling , New York : American Society of Mechanical Engineers .
  • Muñoz-Escalona , P. and Maropoulos , P. 2010 . Integrated optimisation of surface roughness and tool performance when face milling 416 SS . International Journal of Computer Integrated Manufacturing , 23 ( 3 ) : 248 – 256 .
  • Ozel , T. and Karpat , Y. 2005/2004 . Predictive modeling of surface roughness and tool wear in hard turning using regression and neural networks . International Journal of Machine Tools and Manufacture , 45 ( 4–5 ) : 467 – 479 .
  • Qian , L. , Yang , B. and Lei , S. 2008 . Comparing and combining off-line feedrate rescheduling strategies in free-form surface machining with feedrate acceleration and deceleration . Robotics and Computer-Integrated Manufacturing , 24 ( 6 ) : 796 – 803 .
  • Quintana , G. , De Ciurana , J. and Ribatallada , J. 2010 . Surface roughness generation and material removal rate in ball end milling operations . Materials and Manufacturing Processes , 25 ( 6 ) : 386 – 398 .
  • Quintana , G. , Garcia-Romeu , M.L. and Ciurana , J. 2009 . Surface roughness monitoring application based on artificial neural networks for ball-end milling operations . Journal of Intelligent Manufacturing , 22 (4) : 1 – 11 .
  • Samanta , B. 2009 . Surface roughness prediction in machining using soft computing . International Journal of Computer Integrated Manufacturing , 22 ( 3 ) : 257 – 266 .
  • Schulz , H. 1995 . High-speed milling of dies and moulds – cutting conditions and technology . CIRP Annals – Manufacturing Technology , 44 ( 1 ) : 35 – 38 .
  • Swingler , K. 1996 . Applying neural networks: a practical guide , London, San Diego , CA : Academic Press .
  • Thangavel , P. and Selladurai , V. 2008 . An experimental investigation on the effect of turning parameters on surface roughness . International Journal of Manufacturing Research , 3 ( 3 ) : 285 – 300 .
  • Vivancos , J. 2005 . Analysis of factors affecting the high-speed side milling of hardened die steels . Journal of Materials Processing Technology , 162–163 ( SPEC. ISS. ) : 696 – 701 .

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.