Intelligent CNC Tool Path Optimization for Sculptured Surface Machining Through a Virus-Evolutionary Genetic Algorithm

  • Nikolaos A. Fountas
  • Nikolaos M. VaxevanidisEmail author
  • Constantinos I. Stergiou
  • Redha Benhadj-Djilali
Part of the Materials Forming, Machining and Tribology book series (MFMT)


Priorities for manufacturers worldwide include their attempt towards optimizing modern manufacturing systems to satisfy the needs of their customers. Major goal of the proposed study is to present a novel optimization methodology based on Artificial Intelligence using the Virus Theory of Evolution. The methodology implements a Virus-Evolutionary Genetic Algorithm to undertake sculptured surface tool path optimization in terms of geometrical machining error to reflect part quality and machining time to reflect productivity for both 3- and 5-axis sculptured surface machining. The algorithm implements its virus operators to create efficient solution representations, to rabidly reproduce enhanced schemata during the evaluations’ loops, and finally come up with the optimum machining parameters based on the available resources and constraints ought to be imposed. Through a fully automated environment, time-consuming activities and repetitive tasks are no more of the CNC programmers’ concern since the algorithm handles the CAM system’s routines to handle them for its own benefit. The proposed methodology is deemed capable of providing uniform tool paths with low geometric machining error distribution as well as high productivity rates to the best possible extent.


Virus-evolutionary genetic algorithm Tool path generation Sculptured surface machining CAM software CNC programming 


  1. 1.
    Anderson N (1970) Evolutionary significance of virus infection. Nature 227:1346–1347CrossRefGoogle Scholar
  2. 2.
    Budak E, Tunç LT, Alan S, Özgüven HN (2012) Prediction of workpiece dynamics and its effects on chatter stability in milling. CIRP Ann-Manuf Technol 61(1):339–342CrossRefGoogle Scholar
  3. 3.
    Can A, Ünüvar A (2010) A novel iso-scallop tool-path generation for efficient five-axis machining of free-form surfaces. Int J Adv Manuf Technol 51(9–12):1083–1098CrossRefGoogle Scholar
  4. 4.
    Choi BK, Jerard RB (1998) Sculptured surface machining: theory and applications. Kluwer Academic Publishers, DordrechtCrossRefGoogle Scholar
  5. 5.
    Del Prete A, Mazzotta D, Anglani A (2007) Control and optimization of toolpath in metal cutting applications through the usage of computer aided instruments. 8th AITeM Conf Montecatini Terme, p 10–12Google Scholar
  6. 6.
    Drysdale SRL, Rote G, Sturm A (2008) Approximation of an open polygonal curve with a minimum number of circular arcs and biarcs. Comput Geom 41:31–47zbMATHMathSciNetCrossRefGoogle Scholar
  7. 7.
    Duroobi AA, Mohamed JH, Kazem BI, Wenlaing C (2013) Pick-interval scallop height estimation using three types of geometrical end mill cutters on cnc milling machine. Int J Eng Technol 31(8):1580–1591Google Scholar
  8. 8.
    Fountas NA, Vaxevanidis NM, Stergiou CI, Benhadj-Djilali R (2014) Development of a software-automated intelligent sculptured surface machining optimization environment. Int Adv Manuf Technol 75(5–8):909–931CrossRefGoogle Scholar
  9. 9.
    Gilles P, Cohen G, Monies F, Rubio W (2013) Torus cutter positioning in five-axis milling using balance of the transversal cutting force. Int J Adv Manuf Technol 66(5–8):965–973CrossRefGoogle Scholar
  10. 10.
    Goldberg DE (1989) Genetic algorithms in search, optimization, and machine learning. Reading, Massachusetts, Addison-WesleyzbMATHGoogle Scholar
  11. 11.
    Hacene A, Assas M (2011) NURBS interpolation strategies of complex surfaces in high speed machining. Int J CAD/CAM 11(1):1–6Google Scholar
  12. 12.
    Jian C, Li F (2013) An improved virus evolutionary genetic algorithm for workflow mining. J Theor Appl Inform Technol 47(1):406–411Google Scholar
  13. 13.
    Kubota N, Fukuda T, Shimojima K (1996) Virus-evolutionary algorithm for a self-organising manufacturing system. Comp Ind Eng 30(4):1015–1026CrossRefGoogle Scholar
  14. 14.
    Lai XD, Zhou YF, Zhou J, Peng FY, Yan SJ (2003) Geometrical error analysis and control for 5-axis machining of large sculptured surfaces. Int J Adv Manuf Technol 21:110–118Google Scholar
  15. 15.
    Li H, Remus TF, Feng HY (2007) An improved tool path discretization method for five-axis sculptured surface machining. Int J Adv Manuf Technol 33(9–10):994–1000CrossRefGoogle Scholar
  16. 16.
    Lin Z, Fu J, Shen H, Gan W (2014) A generic uniform scallop tool path generation method for five-axis machining of freeform surface. Comput Aided Des 56:120–132CrossRefGoogle Scholar
  17. 17.
    Liu M, Huang Y, Yin L, Guo J, Shao X, Zhang G (2014) Development and implementation of a NURBS interpolator with smooth feedrate scheduling for CNC machine tools. Int J Mach Tools Manuf 87:1–15CrossRefGoogle Scholar
  18. 18.
    López de Lacalle LN, Lamikiz A (2008) Sculptured Surface Machining. In: Davim JP (ed) Machining. Springer, New YorkGoogle Scholar
  19. 19.
    Ma W, He P (1998) B-spline surface local updating with unorganised points. Comput Aided Des 30(11):165–172CrossRefGoogle Scholar
  20. 20.
    Malik S, Wadhwa S (2014) Preventing premature convergence in genetic algorithm using DGCA and elitist technique. Int J Adv Res Comp Sci Soft Eng 4(6):410–418Google Scholar
  21. 21.
    Manav C, Bank HS, Lazoglu I (2013) Intelligent tool path selection via multi-criteria optimization in complex sculptured surface milling. J Intell Manuf 24:349–355CrossRefGoogle Scholar
  22. 22.
    Ponomarev B (2014) Selecting optimal machining strategy parameters when milling complex surfaces by spherical milling cutters. Int J Mech Mechatr Eng 14(1):1–5MathSciNetGoogle Scholar
  23. 23.
    Quinsat Y, Sabourin L, Lartique C (2008) Surface topography in ball end milling process: description of a 3D surface roughness parameter. J Mater Proces Technol 195(1–3):135–143CrossRefGoogle Scholar
  24. 24.
    Shukun C, Li S, Ke D, Kaifeng S, Zhiming A (2012) Research on path optimization technology for free-form surface five-axis NC machining. Adv Mater Res 443–444:202–208Google Scholar
  25. 25.
    Vijayaraghavan A, Sodemann A, Hoover A, Mayor JR, Dornfeld D (2010) Trajectory generation in high-speed, high-precision micromilling using subdivision curves. Int J Mach Tools Manuf 50(4):394–403CrossRefGoogle Scholar
  26. 26.
    Warkentin A, Ismail F, Bedi S (2000) Comparison between multi-point and other 5-axis tool positioning strategies. Int J Mach Tools Manuf 40(2):185–208CrossRefGoogle Scholar
  27. 27.
    Warkentin A, Ismail F, Bedi S (2000) Multi-point tool positioning strategy for 5-axis machining of sculptured surfaces. Comput Aided Geomc Des 17(1):83–100MathSciNetCrossRefGoogle Scholar
  28. 28.
    Yang J, Altintas Y (2015) A generalized on-line estimation and control of five-axis contouring errors of CNC machine tools. Int J Mach Tools Manuf 88:9–23CrossRefGoogle Scholar
  29. 29.
    Yang X (2002) Efficient circular arc interpolation based on active tolerance control. Comput Aided Des 34:1037–1046CrossRefGoogle Scholar
  30. 30.
    Yen SS, Hsu PL (2002) Adaptive feedrate interpolation for parametric curves with confined chord error. Comput Aided Des 34:229–237CrossRefGoogle Scholar
  31. 31.
    Zeroudi N, Fontaine M, Necib K (2012) Prediction of cutting forces in 3-axes milling of sculptured surfaces directly from CAM tool path. J Intell Manuf 23(5):1573–1587CrossRefGoogle Scholar
  32. 32.
    Zhang XF, Xie J, Xie HF, Li LH (2012) Experimental investigation on various tool path strategies influencing surface quality and form accuracy of CNC milled complex freeform surface. Int J Adv Manuf Technol 59:647–654CrossRefGoogle Scholar
  33. 33.
    Zou Q, Zhang J, Deng B, Zhao J (2014) Iso-level tool path planning for free-form surfaces. Comput Aided Des 53:117–125MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Nikolaos A. Fountas
    • 1
    • 3
  • Nikolaos M. Vaxevanidis
    • 2
    Email author
  • Constantinos I. Stergiou
    • 2
  • Redha Benhadj-Djilali
    • 3
  1. 1.School of Pedagogical and Technological Education (ASPETE)Faculty of Mechanical Engineering-Laboratory of Manufacturing Processes and Machine Tools (LMProMaT)AthensGreece
  2. 2.Technological Institute (TEI) of PiraeusMechanical Engineering Department-Laboratory of Advanced Computer-Aided Design and ApplicationsAthensGreece
  3. 3.Faculty of Science, Engineering and Computing (SEC), School of Mechanical and Automotive EngineeringKingston UniversityLondonUK

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