1.

Abburi NR, Dixit US (2006) A knowledge-based system for the prediction of surface roughness in turning process. Robot Comput Integr Manuf 22(4):363–372

2.

Abrão AM, Faria PE, Rubio JC, Reis P, Davim JP (2007) Drilling of fiber reinforced plastics: a review. J Mater Process Technol 186(1–3):1–7

3.

Abu-Mahfouz I (2003) Drilling wear detection and classification using vibration signals and artificial neural network. Int J Mach Tools Manuf 43:707–720

4.

Agapiou JS (1992a) The optimization of machining operations based on a combined criterion-Part 2 Multi-pass operations. J Eng Ind 114:508–513

5.

Agapiou JS (1992b) An optimization of multi-stage machining system, part I: Mathematical solution part 2: The algorithm and application. J Eng Ind 114:524–538

6.

Agapiou JS (1992c) The optimization of machining operation based on a combined criterion, part I: The use of combined objectives in single-pass operations. J Eng Ind 114:500–507

7.

Aggarwal A, Singh H, Kumar P, Singh M (2008) Optimization of multiple quality characteristics for CNC turning under cryogenic cutting environment using desirability function. J Mater Process Technol 205(1–3):42–50

8.

Ahearne E, Byrne G (2008) Simulation of the local kinematics in rotational grinding. CIRP Ann Manuf Technol 57(1):333–336

9.

Alagumurthi N, Palaniradja K, Soundararajan V (2006) Optimization of grinding process through design of experiment (DOE): a comparative study. Mater Manuf Process 21(1):19–21

10.

Al-Ahmari AMA (2007) Predictive machinability models for a selected hard material in turning operations. J Mater Process Technol 190(1–3):305–311

11.

Al-Aomar R, Al-Okaily A (2006) A GA-based parameter design for single machine turning process with high-volume production. Comput Ind Eng 50(3):317–337

12.

Ali YM, Zhang LC (2004) A fuzzy model for predicting burns in surface grinding of steel. Int J Mach Tools Manuf 44(5):563–571

13.

Amiolemhen E, Ibhadode AOA (2004) Application of genetic algorithms—determination of the optimal machining parameters in the conversion of a cylindrical bar stock into a continuous finished profile. Int J Mach Tools Manuf 44(12–13):1403–1412

14.

Amitay G (1981) Adaptive control optimization of grinding. J Eng Ind 103(1):103–108

15.

António CAC, Davim JP (2002) Optimal cutting conditions in turning of particulate metal matrix composites based on experiment and a genetic search model. Compos Part A Appl Sci Manuf 33(2):213–219

16.

Armarego EJA, Smith AJR, Wang J (1994) Computer-aided constrained optimization analyses and strategies for multipass helical tooth milling operations. CIRP Ann Manuf Technol 43(1):437–442

17.

Arul S, Raj DS, Vijayaraghavan L, Malhotra SK, Krishnamurthy R (2006) Modeling and optimization of process parameters for defect toleranced drilling of GFRP composites. Mater Manuf Process 21(4):357–365

18.

Arul S, Vijayaraghavan L, Malhotra SK (2007) Online monitoring of acoustic emission for quality control in drilling of polymeric composites. J Mater Process Technol 185(1–3):184–190

19.

Aslan E, Camuscu N, Birgoren B (2007) Design optimization of cutting parameters when turning hardened AISI 4140 steel (63 HRC) with Al_{2}O_{3} + TiCN mixed ceramic tool. Mater Des 28:1618–1622

20.

Asokan P, Baskar N, Babu K (2005) Optimization of surface grinding operations using particle swarm optimization technique. J Manuf Sci Eng 127(4):885–892

21.

Audy J (2008) A study of computer-assisted analysis of effects of drill geometry and surface coating on forces and power in drilling. J Mater Process Technol 204(1–3):130–138

22.

Aykut Ş, Gölcü M, Semiz S, Ergür HS (2007) Modeling of cutting forces as function of cutting parameters for face milling of satellite 6 using an artificial neural network. J Mater Process Technol 190(1–3):199–203

23.

Baek DK, Ko TJ, Kim HS (2001) Optimization of feedrate in a face milling operation using a surface roughness model. Int J Mach Tools Manuf 41(3):451–462

24.

Bağci E, Ozcelik B (2006a) Analysis of temperature changes on the twist drill under different drilling conditions based on Taguchi method during dry drilling of Al 7075–T651. Int J Adv Manuf Technol 29(7–8):629–636

25.

Bağci E, Ozcelik B (2006b) Investigation of the effect of drilling conditions on the twist drill temperature during step-by-step and continuous dry drilling. Mater Des 27(6):446–454

26.

Balaji AK, Ghosh R, Fang XD, Stevenson R, Jawahir IS (2006) Performance-based predictive models and optimization methods for turning operations and applications: part 2-Assessment of chip forms/chip breakability. J Manuf Process 8(2):144–158

27.

Balykov AV (2003) Optimization of diamond drilling using an extreme experimental design. Glass Ceram 60(7–8):213–216

28.

Bandyopadhyay S, Gokhale H, Sundar JKS, Sundararajan G, Joshi SV (2005) A statistical approach to determine process parameter impact in Nd:YAG laser drilling of IN718 and Ti-6Al-4V sheets. Opt Lasers Eng 43(2):163–182

29.

Baro PK, Joshi SS, Kapoor SG (2005) Modeling of cutting forces in a face-milling operation with self-propelled round insert milling cutter. Int J Mach Tools Manuf 45(7–8):831–839

30.

Basak H, Goktas HH (2009) Burnishing process on al-alloy and optimization of surface roughness and surface hardness by fuzzy logic. Mater Des 30(4):1275–1281

31.

Basak S, Dixit US, Davim JP (2007) Application of radial basis function neural networks in optimization of hard turning of AISI D2 cold-worked steel with a ceramic tool. Proc Inst Mech Eng Part B J Eng Manuf 221:987–998

32.

Basavarajappa S, Chandramohan G, Davim JP (2008) Some studies on drilling of hybrid metal matrix composites based on Taguchi techniques. J Mater Process Technol 196(1–3):332–338

33.

Baskar N, Asokan P, Saravanan R, Prabhaharan G (2006) Selection of optimal machining parameters for multi-tool milling operations using a memetic algorithm. J Mater Process Technol 174:239–249

34.

Baykasoglu A, Dereli T (2002) Novel algorithm approach to generate the ‘number of passes’ and ‘depth of cuts’ for the optimization routines of multi pass machining. Int J Prod Res 40:1549–1565

35.

Benardos PG, Vosniakos GC (2002) Prediction of surface roughness in CNC face milling using neural networks and Taguchi’s design of experiments. Robot Comput Integr Manuf 18(5–6):343–354

36.

Bhattacharyya K, Mukherjee A (2006) Modeling and simulation of centerless grinding of ball bearings. Simul Modell Pract Theory 14(7):971–988

37.

Bigerelle M, Hagege B, El-Mansori M (2008) Mechanical modeling of micro-scale abrasion in superfinish belt grinding. Tribol Int 41(11):992–1001

38.

Biglari FR, Fang XD (1995) Real-time fuzzy logic control for maximizing the tool life of small-diameter drills. Fuzzy Sets Syst 72:91–101

39.

Bouacha K, Yallese MA, Mabrouki T, Rigal JF (2010) Statistical analysis of surface roughness and cutting forces using response surface methodology in hard turning of AISI 52100 bearing steel with CBN tool. Int J Refra Met Hard Mater 28(3):349–361

40.

Bouzid W (2005) Cutting parameter optimization to minimize production time in high speed turning. J Mater Process Technol 161(3):388–395

41.

Brinksmeier E, Tonshoff HK, Czenkusch C, Heinzel C (1998) Modeling and optimization of grinding processes. J Intell Manuf 9:303–314

42.

Brinksmeier E, Aurich JC, Govekar E, Heinzel C, Hoffmeister HW, Klocke F, Peters J, Rentsch R, Stephenson DJ, Uhlmann E, Weinert K, Wittmann M (2006) Advances in modeling and simulation of grinding processes. CIRP Ann Manuf Technol 55(2):667–696

43.

Brinksmeier E, Heinzel C, Bleil N (2009) Superfinishing and grind-strengthening with elastic bonding system. J Mater Process Technol 209(20):6117–6123

44.

Budak E, Tekeli A (2005) Maximizing chatter free material removal rate in milling through optimal selection of axial and radial depth of cut pairs. CIRP Ann Manuf Technol 54(1):353–356

45.

Budak E, Ozturk E, Tunc LT (2009) Modeling and simulation of 5-axis milling processes. CIRP Ann Manuf Technol 58(1):347–350

46.

Cakir MC, Gurarda A (1998) Optimization and graphical representation of machining conditions in multi-pass turning operations. Comput Integr Manuf Syst 11(3):157–170

47.

Cakir MC, Gurarda A (2000) Optimization of machining conditions for multi-tool milling operations. Int J Prod Res 38(15):3537–3552

MATH48.

Chakraborty P, Asfour S, Cho S, Onar A, Lynn M (2008) Modeling tool wear progression by using mixed effects modeling technique when end-milling AISI 4340 steel. J Mater Process Technol 205(1–3):190–202

49.

Chandrasekaran M, Muralidhar M, Krishna CM, Dixit US (2010) Application of soft computing techniques in machining performance prediction and optimization: a literature review. Int J Adv Manuf Technol 46(5–8):445–464

50.

Chang PC, Hsieh JC, Wang CY (2007) Adaptive multi-objective genetic algorithms for scheduling of drilling operation in printed circuit board industry. Appl Soft Comput 7(3):800–806

51.

Chang SH, Farris TN, Chandrasekar S (2008) Experimental analysis on evolution of superfinished surface texture. J Mater Process Technol 203(1–3):365–371

52.

Chen MC (2004) Optimizing machining economics models of turning operations using the scatter search approach. Int J Prod Res 42:2611–2625

53.

Chen MC , Chen KY (2003) Optimization of multipass turning operations with genetic algorithms: a note. Int J Prod Res 41(14):3385–3388

54.

Chen JC, Savage M (2001) A fuzzy-net-based multilevel in-process surface roughness recognition system in milling operations. Int J Adv Manuf Technol 17(9):670–676

55.

Chen MC, Tsai DM (1996) A simulated annealing approach for optimization of multi-pass turning operations. Int J Prod Res 34(10):2803–2825

MathSciNetMATH56.

Chen YH, Lee YS, Fang SC (1998) Optimal cutter selection and machining plane determination for process planning and NC machining of complex surfaces. J Manuf Syst 17(5):371–388

57.

Chen C, Sakai S, Inasaki I (1991) Lapping of advanced ceramics. Mater Manuf Process 6(2):211–226

58.

Chien WT, Tsai CS (2003) The investigation on the prediction of tool wear and determination of optimum cutting conditions in machining 17-4PH stainless steel. J Mater Process Technol 140(1–3):340–345

59.

Ching-Kao C, Lu HS (2007) The optimal cutting-parameter selection of heavy cutting process in side milling for SUS304 stainless steel. Int J Adv Manuf Technol 34(5–6):440–447

60.

Choi JG, Yang MY (1999) In-process prediction of cutting depths in end milling. Int J Mach Tools Manuf 39(5):705–721

61.

Choi TJ, Subrahmanya N, Li H, Shin YC (2008a) Generalized practical models of cylindrical plunge grinding processes. Int J Mach Tools Manuf 48(1):61–72

62.

Choi YJ, Park MS, Chu CN (2008b) Prediction of drill failure using features extraction in time and frequency domains of feed motor current. Int J Mach Tools Manuf 48:29–39

63.

Chua MS, Loh HT, Wong YS, Rahman M (1991) Optimization of cutting conditions for multi-pass turning operations using sequential quadratic programming. J Mater Process Technol 28(1–2):253–262

64.

Cus F, Balic J (2003) Optimization of cutting process by GA approach. Robot Comput Integr Manuf 19:113–121

65.

Cus F, Milfelner M, Balic J (2006) An intelligent system for monitoring and optimization of ball-end milling process. J Mater Process Technol 175(1–3):90–97

66.

Davim JP (2001) A note on the determination of optimal cutting conditions for surface finish obtained in turning using design of experiments. J Mater Process Technol 116(2–3):305–308

67.

Davim JP (2003) Design of optimization of cutting parameters for turning metal matrix composites based on the orthogonal arrays. J Mater Process Technol 132:340–344

68.

Davim JP, António CAC (2001a) Optimal drilling of particulate metal matrix composites based on experimental and numerical procedures. Int J Mach Tools Manuf 41(1):21–31

69.

Davim JP, António CAC (2001b) Optimization of cutting conditions in machining of aluminium matrix composites using a numerical and experimental model. J Mater Process Technol 112(1):78–82

70.

Davim JP, Gaitonde VN, Karnik SR (2008) Investigations into the effect of cutting conditions on surface roughness in turning of free machining steel by ANN models. J Mater Process Technol 205(1–3):16–23

71.

de Lacalle LNL, Lamikiz A, Sánchez JA, Arana JL (2007) The effect of ball burnishing on heat-treated steel and Inconel 718 milled surfaces. Int J Adv Manuf Technol 32(9–10):958–968

72.

Dhavalikar MN, Kulkarni MS, Mariappan V (2003) Combined Taguchi and dual response method for optimization of a centerless grinding operation. J Mater Process Technol 132:90–94

73.

Doman DA, Warkentin A, Bauer R (2009) Finite element modeling approaches in grinding. Int J Mach Tools Manuf 49(2):109–116

74.

Drazumeric R, Krajnik P, Vrabic R, Meyer B, Butala P, Kosel F, Kopac J (2010) Modeling of grinding gap macro geometry and workpiece kinematics in throughfeed centreless grinding. J Mater Process Technol 210(1):104–109

75.

Dubey AK (2008a) A hybrid approach for multi-performance optimization of the electro chemical honing process. Int J Adv Manuf Technol. doi:

10.1007/s00170-008-1422-8
76.

Dubey AK (2008b) Multi-performance modeling and optimization control strategies for electro chemical honing: a critical evaluation. Int J Adv Manuf Technol. doi:

10.1007/s00170-008-1477-6
77.

Dubey AK (2009) Multi-response optimization of electro chemical honing using utility-based Taguchi approach. Int J Adv Manuf Technol 41(7–8):749–759

78.

Dutta RK, Paul S, Chattopadhyay AB (2006) The efficacy of back propagation neural network with delta bar delta learning in predicting the wear of carbide inserts in face milling. Int J Adv Manuf Technol 31(5–6):434–442

79.

Dvivedi A, Kumar P (2007) Surface quality evaluation in ultrasonic drilling through the Taguchi technique. Int J Adv Manuf Technol 34(1–2):131–140

80.

Ee KC, Li PX, Balaji AK, Jawahir IS, Stevenson R (2006) Performance-based predictive models and optimization methods for turning operations and applications: part 1. Tool wear/tool life in turning with coated grooved tools. J Manuf Process 8(1):54–66

81.

Elhachimi M, Torbaty S, Joyot P (1999) Mechanical modeling of high speed drilling. 1: predicting torque and thrust. Int J Mach Tools Manuf 39(4):553–568

82.

El-Mounayri H, Kishawy H, Briceno J (2005) Optimization of CNC ball end milling: a neural network-based model. J Mater Process Technol 166(1):50–62

83.

El-Taweel TA, El-Axir MH (2009) Analysis and optimization of the ball burnishing process through the Taguchi technique. Int J Adv Manuf Technol 41(3–4):301–310

84.

El-Tayeb NSM, Low KO, Brevern PV (2008) Enhancement of surface quality and tribological properties using ball burnishing process. Mach Sci Tech 12(2):234–248

85.

El-Wahab AI, Abdelhay AM (1998) A new algorithm and tool design for CNC profile burnishing. Int J Prod Res 36(7):1977–1985

MATH86.

Ertunc HM, Loparo KA, Ocak H (2001) Tool wear condition monitoring in drilling operations using hidden Markov models (HMMs). Int J Mach Tools Manuf 41(9):1363–1384

87.

Feng CX, Wang X (2002) Development of empirical models for surface roughness prediction in finish turning. Int J Adv Manuf Technol 20:348–356

88.

Feng CX, Wang X, Yu Z (2002) Neural networks modeling of honing surface roughness parameters defined by ISO 13565. J Manuf Syst 21(5):395–408

89.

Feng CXJ, Yu ZGS, Wang JHJ (2005) Validation and data splitting in predictive regression modeling of honing surface roughness data. Int J Prod Res 43(8):1555–1571

90.

Fernandes M, Cook C (2006) Drilling of carbon composites using a one shot drill bit. Part II: empirical modeling of maximum thrust force. Int J Mach Tools Manuf 46(1):76–79

91.

Fernandes MH, Garitaonandia I, Albizuri J, Hernández JM, Barrenetxea D (2009) Simulation of an active vibration control system in a centerless grinding machine using a reduced updated FE model. Int J Mach Tools Manuf 49(3–4):239–245

92.

Fontaine M, Moufki A, Devillez A, Dudzinski D (2007a) Modeling of cutting forces in ball-end milling with tool–surface inclination: Part I. Predictive force model and experimental validation. J Mater Process Technol 189:73–84

93.

Fontaine M, Devillez A, Moufki A, Dudzinski D (2007b) Modeling of cutting forces in ball-end milling with tool–surface inclination: Part II. Influence of cutting conditions, run-out, ploughing and inclination angle. J Mater Process Technol 189(1–3):85–96

94.

Gaitonde VN, Karnik SR, Achyutha BT, Siddeswarappa B (2007) Methodology of Taguchi optimization for multi-objective drilling problem to minimize burr size. Int J Adv Manuf Technol 34(1–2):1–8

95.

Gaitonde VN, Karnik SR, Achyutha BT, Siddeswarappa B (2008a) Taguchi optimization in drilling of AISI 316L stainless steel to minimize burr size using multi-performance objective based on membership function. J Mater Process Technol 202(1–3):374–379

96.

Gaitonde VN, Karnik SR, Achyutha BT, Siddeswarappa B (2008b) Genetic algorithm-based burr size minimization in drilling of AISI 316L stainless steel. J Mater Process Technol 197(1–3):225–236

97.

Gaitonde VN, Karnik SR, Davim JP (2008c) Taguchi multiple-performance characteristics optimization in drilling of medium density fibreboard (MDF) to minimize delamination using utility concept. J Mater Process Technol 196(1–3):73–78

98.

Gaitonde VN, Karnik SR, Davim JP (2008d) Prediction and minimization of delamination in drilling of medium-density fiberboard (MDF) using response surface methodology and taguchi design. Mater Manuf Processes 23(4):377–384

99.

Gaitonde VN, Karnik SR, Rubio JC, Correia AE, Abrão AM, Davim JP (2008e) Analysis of parametric influence on delamination in high-speed drilling of carbon fiber reinforced plastic composites. J Mater Process Technol 203(1–3):431–438

100.

Gaitonde VN, Karnik SR, Davim JP (2009) Multiperformance optimization in turning of free-machining steel using taguchi method and utility concept. J Mater Eng Perform 18(3):231–236

101.

Garg S, Pal SK, Chakraborty D (2007) Evaluation of the performance of back propagation and radial basis function neural networks in predicting the drill flank wear. Neural Comput Appl 16:407–417

102.

Ghaiebi H, Solimanpur M (2007) An ant algorithm for optimization of hole-making operations. Comput Ind Eng 52:308–319

103.

Ghani JA, Choudhury IA, Hassan HH (2004) Application of Taguchi method in the optimization of end milling parameters. J Mater Process Technol 145(1):84–92

104.

Ghosh N, Ravi YB, Mukhopadyay S, Paul S, Mohanty AR, Chattopadyay AB (2007) Estimation of tool wear during CNC milling using neural network-based sensor fusion. Mech Syst Signal Process 21:466–479

105.

Gómez MP, Hey AM, Ruzzante JE, D’Attellis CE (2010) Tool wear evaluation in drilling by acoustic emission. Phys Procedia 3(1):819–825

106.

Gopal AV, Rao PV (2003) Selection of optimum conditions for maximum material removal rate with surface finish and damage as constraints in SiC grinding. Int J Mach Tools Manuf 43(13):1327–1336

107.

Gopalakrishnan B, Al-Khayyal F (1991) Machine parameter selection for turning with constraints: an analytical approach based on geometric programming. Int J Prod Res 29(9):1897–1908

MATH108.

Govindhasamy JJ, McLoone SF, Irwin GW, French JJ, Doyle RP (2005) Neural modeling, control and optimization of an industrial grinding process. Control Eng Pract 13(10):1243–1258

109.

Guevarra DS, Kyusojin A, Isobe H, Kaneko Y (2002) Development of a new lapping method for high precision ball screw (2nd report): design and experimental study of an automatic lapping machine with in-process torque monitoring system. Precis Eng 26(4):389–395

110.

Guibert N, Paris H, Rech J, Claudin C (2009) Identification of thrust force models for vibratory drilling. Int J Mach Tools Manuf 49(9):730–738

111.

Guo YB, Zhang Y, Zhong JA, Syoji K (2002) Optimization of honing wheel structure parameters in ultra-precision plane honing. J Mater Process Technol 129(1–3):96–100

112.

Guo C, Campomanes M, Mcintosh D, Becze C, Gree S, Malkin S (2003) Optimization of continuous dress creep-feed form grinding process. CIRP Ann Manuf Technol 52(1):259–262

113.

Guo C, Campomanes M, Mcintosh D, Becze C, Malkin S (2004) Model-based monitoring and control of continuous dress creep-feed form grinding. CIRP Ann Manuf Technol 53(1):263–266

114.

Gupta R, Batra JL, Lal GK (1995) Determination of optimal subdivision of depth of cut in multi-pass turning with constraints. Int J Prod Res 33(9):2555–2565

MATH115.

Gupta R, Shishodia KS, Sekhon GS (2001) Optimization of grinding process parameters using enumeration method. J Mater Process Technol 112(1):63–67

116.

Gurel S, Akturk MS (2007) Considering manufacturing cost and scheduling performance on a CNC turning machine. Eur J Oper Res 177(1):325–343

MATH117.

Haber RE, Haber-Haber R, Jiménez A, Galán R (2009) An optimal fuzzy control system in a network environment based on simulated annealing-an application to a drilling process. Appl Soft Comput 9(3):889–895

118.

Haq AN, Marimuthu P, Jeyapaul R (2008) Multi response optimization of machining parameters of drilling Al/SiC metal matrix composite using grey relational analysis in the Taguchi method. Int J Adv Manuf Technol 37(3–4):250–255

119.

Hashimoto F, Lahoti GD (2004) Optimization of set-up conditions for stability of the centerless grinding process. CIRP Ann Manuf Technol 53(1):271–274

120.

Hashmi K, Graham ID, Mills B (2000) Fuzzy logic based data selection for the drilling process. J Mater Process Technol 108:55–61

121.

Hassan AM, Sulieman AD (1999) Improvement in the wear resistance of brass components by the ball burnishing process. J Mater Process Technol 96(1–3):73–80

122.

Hassan AM, Al-Jalil HF, Ebied AA (1998) Burnishing force and number of ball passes for the optimum surface finish of brass components. J Mater Process Technol 83:176–179

123.

Heisel U, Luik M, Eisseler R, Schaal M (2005) Prediction of parameters for the burr dimensions in short-hole drilling. CIRP Ann Manuf Technol 54(1):79–82

124.

Hekman KA, Liang SY (1999) Feed rate optimization and depth of cut control for productivity and part parallelism in grinding. Mechatronics 9(5):447–462

125.

Ho WH, Tsai JT, Lin BT, Chou JH (2009) Adaptive network-based fuzzy inference system for prediction of surface roughness in end milling process using hybrid Taguchi-genetic learning algorithm. Expert Syst Appl 36(2):3216–3222

126.

Horng JT, Chiang KT (2008) A grey and fuzzy algorithms integrated approach to the optimization of turning Hadfield steel with Al_{2}O_{3}/TiC mixed ceramic tool. J Mater Process Technol 207(1–3):89–97

127.

Hui YV, Leung LC, Linn R (2001) Optimal machining conditions with cost of quality and tool maintenance for turning. Int J Prod Res 39(4):647–665

MATH128.

Hundt W, Kuster F, Rehsteiner F (1997) Model-based AE monitoring of the grinding process. CIRP Ann Manuf Technol 46(1):243–247

129.

Ibrahim AA, Rabbo SMA, El-Axir MH, Ebied AA (2009) Center rest balls burnishing parameters adaptation of steel components using fuzzy logic. J Mater Process Technol 209(5):2428–2435

130.

Iliescu D, Gehin D, Gutierrez ME, Girot F (2010) Modeling and tool wear in drilling of CFRP. Int J Mach Tools Manuf 50(2):204–213

131.

Inasaki I (1991) Monitoring and optimization of internal grinding process. CIRP Ann Manuf Technol 40(1):359–362

132.

Iqbal A, Dar NU, He N, Hammouda MMI, Li L (2009) Self-developing fuzzy expert system: a novel learning approach, fitting for manufacturing domain. J Intell Manuf 31(5–6):434–442. doi:

10.1007/s10845-009-0252-3l
133.

Jadoun RS, Kumar P, Mishra BK (2009) Taguchi’s optimization of process parameters for production accuracy in ultrasonic drilling of engineering ceramics. Prod Eng 3(3):243–253

134.

Jawahir IS, Wang X (2007) Development of hybrid predictive models and optimization techniques for machining operations. J Mater Process Technol 185(1–3):46–59

135.

Jayakumar T, Mukhopadhyay CK, Venugopal S, Mannan SL, Raj B (2005) A review of the application of acoustic emission techniques for monitoring forming and grinding processes. J Mater Process Technol 159(1):48–61

136.

Jiang Q, Ge Z (2002) Simulation on topography of superfinished roller surfaces. Sci China B: Chem 45(2):122–126

137.

Jiao Y, Lei S, Pei ZJ, Lee ES (2004) Fuzzy adaptive networks in machining process modeling: surface roughness prediction for turning operations. Int J Mach Tools Manuf 44(15):1643–1651

138.

Johansen L, Lund E (2009) Optimization of laminated composite structures using delamination criteria and hierarchical models. Struct Multidiscip Optim 38(4):357–375

139.

Kadirgama K, Abou-El-Hossein KA, Mohammad B, Habeeb H (2007) Statistical model to determine surface roughness when milling hastelloy C-22HS. J Mech Sci Technol 21(10):1651–1655

140.

Karnik SR, Gaitonde VN, Rubio JC, Correia AE, Abrão AM, Davim JP (2008) Delamination analysis in high speed drilling of carbon fiber reinforced plastics (CFRP) using artificial neural network model. Mater Des 29(9):1768–1776

141.

Karpat Y, Özel T (2007) Multi-objective optimization for turning processes using neural network modeling and dynamic-neighborhood particle swarm optimization. Int J Adv Manuf Technol 35(3–4):234–247

142.

Karthikeyan R, Jaiganesh S, Pai BC (2002) Optimization of drilling characteristics for Al/SiCp composites using fuzzy/GA. Metals Mater Int 8(2):163–168

143.

Kee PK (1996) Development of constrained optimization analyses and strategies for multi-pass rough turning operations. Int J Mach Tools Manuf 36(1):115–127

144.

Kersting P, Zabel A (2009) Optimizing NC-tool paths for simultaneous five-axis milling based on multi-population multi-objective evolutionary algorithms. Adv Eng Softw 40(6):452–463

MATH145.

Khajavi AN, Komanduri R (1993) On multisensor approach in drill wear monitoring. CIRP Ann Manuf Technol 42:71–74

146.

Kiliç SE, Cogun C, Şen DT (1993) A computer-aided graphical technique for the optimization of machining conditions. Comput Ind 22(3):319–326

147.

Kilickap E (2010a) Optimization of cutting parameters on delamination based on Taguchi method during drilling of GFRP composite. Expert Syst Appl 37(8):6116–6122

148.

Kilickap E (2010b) Modeling and optimization of burr height in drilling of Al-7075 using Taguchi method and response surface methodology. Int J Adv Manuf Technol. doi:

10.1007/s00170-009-2469-x
149.

Kim GH (2002) Evaluation of pre-estimation model to the in process surface roughness for grinding operations. Int J Korean Soc Precis Eng 3:24–30

150.

Kim HY, Ahn JH (2002) Chip disposal state monitoring in drilling using neural network based spindle motor power sensing. Int J Mach Tools Manuf 42(10):1113–1119

MathSciNet151.

Kim JD, Choi MS (1995a) A study on the optimization of the cylindrical lapping process for engineering fine-ceramics (Al_{2}O_{3}) by the statistical design method. J Mater Process Technol 52(2–4):368–385

152.

Kim JD, Choi MS (1995b) Stochastic approach to experimental analysis of cylindrical lapping process. Int J Mach Tools Manuf 35(1):51–59

153.

Kim D, Ramulu M (2004) Drilling process optimization for graphite/bismaleimide–titanium alloy stacks. Compos Struct 63(1):101–114

154.

Kim J, Min S, Dornfeld DA (2001) Optimization and control of drilling burr formation of AISI 304L and AISI 4118 based on drilling burr control charts. Int J Mach Tools Manuf 41(7):923–936

155.

Kim SS, Kim IH, Mani V, Kim HJ (2008) Real-coded genetic algorithm for machining condition optimization. Int J Adv Manuf Technol 38:884–895

156.

Kolahan F, Liang M (1996) A tabu search approach to optimization of drilling operations. Comput Ind Eng 31(1–2):371–374

157.

Korzynski M (2007) Modeling and experimental validation of the force–surface roughness relation for smoothing burnishing with a spherical tool. J Mach Tools Manuf 47:1956–1964

158.

Korzynski M, Pacana A (2010) Centreless burnishing and influence of its parameters on machining effects. J Mater Process Technol 210(9):1217–1223

159.

Kovacic M, Balic J, Brezocnik M (2004) Evolutionary approach for cutting forces prediction in milling. J Mater Process Technol 155–156:1647–1652

160.

Krishna AG (2007) Optimization of surface grinding operations using a differential evolution approach. J Mater Process Technol 183:202–209

161.

Kuar AS, Doloi B, Bhattacharya B (2006) Modeling and analysis of pulsed Nd:YAG laser machining characteristics during micro-drilling of zirconia (ZrO_{2}). Int J Mach Tools Manuf 46(12–13):1301–1310

162.

Kurt M, Bağci E, Kaynak Y (2009) Application of Taguchi methods in the optimization of cutting parameters for surface finish and hole diameter accuracy in dry drilling processes. Int J Adv Manuf Technol 40(5–6):458–469

163.

Kwak JS (2005) Application of Taguchi and response surface methodologies for geometric error in surface grinding process. Int J Mach Tools Manuf 45(3):327–334

164.

Kwon Y, Fischer GW, Tseng TL (2002) Fuzzy neuron adaptive modeling to predict surface roughness under process variations in CNC turning. J Manuf Syst 21(6):440–450

165.

Langella A, Nele L, Maio A (2005) A torque and thrust prediction model for drilling of composite materials. Compos Part A Appl Sci Manuf 36(1):83–93

166.

Laouar L, Hamadache H, Saad S, Bouchelaghem A, Mekhilef S (2009) Mechanical surface treatment of steel-Optimization parameters of regime. Phys Procedia 2(3):1213–1221

167.

Lauderbaugh LK (2009) Analysis of the effects of process parameters on exit burrs in drilling using a combined simulation and experimental approach. J Mater Process Technol 209(4):1909–1919

168.

Lee CW, Shin YC (2000) Evolutionary modeling and optimization of grinding process. Int J Prod Res 38(12):2787–2813

169.

Lee BY, Tarng YS (2000) Cutting-parameter selection for maximizing production rate or minimizing production cost in multistage turning operations. J Mater Process Technol 105(1–2):61–66

170.

Lee SG, Tam SC, Loh NH (1993) Ball burnishing of 316 l stainless steel. J Mater Process Technol 37:241–251

171.

Lee BY, Liu HS, Tarng YS (1998) Modeling and optimization of drilling process. J Mater Process Technol 74(1–3):149–157

172.

Li XP, Li HZ (2004) Theoretical modeling of cutting forces in helical end milling with cutter runout. Int J Mech Sci 46(9):1399–1414

MATH173.

Li HZ, Zhang WB, Li XP (2001) Modeling of cutting forces in helical end milling using a predictive machining theory. Int J Mech Sci 43(8):1711–1730

MATH174.

Li GF, Wang LS, Yang LB (2002) Multi-parameter optimization and control of the cylindrical grinding process. J Mater Process Technol 129(1–3):232–236

175.

Liang M, Mgwatu M, Zuo M (2001) Integration of cutting parameter selection and tool adjustment decision for multi-pass turning. Int J Adv Manuf Technol 17:861–869

176.

Liao TW, Chen LJ (1994) A neural network approach for grinding processes: Modeling and optimization. Int J Mach Tools Manuf 34(7):919–937

MathSciNet177.

Lin SC, Ting CJ (1999) Drill wear monitoring using neural networks. Int J Adv Manuf Technol 36:465–475

178.

Liu X, Cheng K (2005) Modeling the machining dynamics of peripheral milling. Int J Mach Tools Manuf 45(11):1301–1320

MathSciNet179.

Liu HS, Lee BY, Tarang YS (2000) In-process prediction of corner wear in drilling operations. Int J Adv Manuf Technol 101:152–158

180.

Liu Q, Chen X, Wang Y, Gindy N (2008) Empirical modeling of grinding force based on multivariate analysis. J Mater Process Technol 203(1–3):420–430

181.

Lizarralde R, Barrenetxea D, Gallego I, Marquinez JI, Bueno R (2005) Practical application of new simulation methods for the elimination of geometric instabilities in centerless grinding. CIRP Ann Manuf Technol 54(1):273–276

182.

Lo SP (2003) An adaptive-network based fuzzy inference system for prediction of workpiece surface roughness in end milling. J Mater Process Technol 142(3):665–675

183.

Loh NH, Tam SC, Miyazawa S (1989a) A study of the effects of ball-burnishing parameters on surface roughness using factorial design. J Mech Work Technol 18:53–61

184.

Loh NH, Tam SC, Miyazawa S (1989b) Optimization of the surface finish produced by ball burnishing. J Mech Work Technol 19(1):101–107

185.

Lu HS, Chang CK, Hwang NC, Chung CT (2009) Grey relational analysis coupled with principal component analysis for optimization design of the cutting parameters in high-speed end milling. J Mater Process Technol 209(8):3808–3817

186.

Mahdy MAM (2001) Economic drilling conditions for a given deburring radius. J Mater Process Technol 110(2):197–205

187.

Mani A, Patvardhan C (2010) Solving ceramic grinding optimization problem by adaptive quantum evolutionary algorithm. In: Proceedings of international conference intelligence system, model simulation, Liverpool, pp 43–48

188.

Manna A, Bhattacharyya B (2004) Investigation for optimal parametric combination for achieving better surface finish during turning of Al/SiC-MMC. Int J Adv Manuf Technol 23:658–665

189.

Manna A, Salodkar S (2008) Optimization of machining conditions for effective turning of E0300 alloy steel. J Mater Process Technol 203(1–3):147–153

190.

Mauch CA, Lauderbaugh LK (1991) Modeling the drilling process—an analytical model to predict thrust force and torque. Precis Eng 13(3):233

191.

Merdol SD, Altintas Y (2008) Virtual cutting and optimization of three-axis milling processes. Int J Mach Tools Manuf 48(10):1063–1071

192.

Messaoud A, Weihs C (2009) Monitoring a deep hole drilling process by nonlinear time series modeling. J Sound Vib 321(3–5):620–630

193.

Michael PC, Saka N, Rabinowicz E (1998) Burnishing and adhesive wear of an electrically conductive polyester-carbon film. Wear 132:265–285

194.

Mohan NS, Kulkarni SM, Ramachandra A (2007) Delamination analysis in drilling process of glass fibre reinforced plastic (GFRP) composite materials. J Mater Process Technol 186(1–3):265–271

195.

Molinari A, Nouari M (2002) Modeling of tool wear by diffusion in metal cutting. Wear 252(1–2):135–149

196.

Mukherjee I, Ray PK (2006) A review of optimization techniques in metal cutting processes. Comput Ind Eng 50(1–2):15–34

197.

Mukherjee I, Ray PK (2008a) A systematic solution methodology for inferential multivariate modeling of industrial grinding process. J Mater Process Technol 196(1–3):379–392

198.

Mukherjee I, Ray PK (2008b) Optimal process design of two-stage multiple responses grinding processes using desirability functions and metaheuristic technique. Appl Soft Comput 8(1):402–421

199.

Muthukrishnan N, Davim JP (2009) Optimization of machining parameters of Al/SiC-MMC with ANOVA and ANN analysis. J Mater Process Technol 209(1):225–232

200.

Nalbant M, Gökkaya H, Sur G (2007) Application of Taguchi method in the optimization of cutting parameters for surface roughness in turning. Mater Des 28(4):1379–1385

201.

Nandi AK, Banerjee MK (2005) FBF-NN-based modeling of cylindrical plunge grinding process using a GA. J Mater Process Technol 162–163:655–664

202.

Nandi AK, Davim JP (2009) A study of drilling performances with minimum quantity of lubricant using fuzzy logic rules. Mechatronics 19:218–232

203.

Nandi AK, Pratihar DK (2004a) Automatic design of fuzzy logic controller using a genetic algorithm—to predict power requirement and surface finish in grinding. J Mater Process Technol 148(3):288–300

MathSciNet204.

Nandi AK, Pratihar DK (2004b) An expert system based on FBFN using a GA to predict surface finish in ultra-precision turning. J Mater Process Technol 155–156:1150–1156

205.

Natarajan U, Saravanan R, Periasamy VM (2006) Application of particle swarm optimization in artificial neural network for prediction of tool life. Int J Adv Manuf Technol 28:1084–1088

206.

Neagu-Ventzel S, Cioc S, Marinescu I (2006) A wear model and simulation of superfinishing process: analysis for the superfinishing of bearing rings. Wear 260(9–10):1061–1069

207.

Nian CY, Yang WH, Tarng YS (1999) Optimization of turning operations with multiple performance characteristics. J Mater Process Technol 95(1–3):90–96

208.

Nouari M, List G, Girot F, Gehin D (2005) Effect of machining parameters and coating on wear mechanisms in dry drilling of aluminium alloys. Int J Mach Tools Manuf 45(12–13):1436–1442

209.

Ojha DK, Dixit US, Davim JP (2009) A soft computing based optimization of multi-pass turning processes. Int J Mater Prod Technol 35:145–166

210.

Öktem H, Erzurumlu T, Çöl M (2006) A study of the Taguchi optimization method for surface roughness in finish milling of mold surfaces. Int J Adv Manuf Technol 28(7–8):694–700

211.

Onwubolu GC (2006a) Selection of drilling operations parameters for optimal tool loading using integrated response surface methodology: a Tribes approach. Int J Prod Res 44(5):959–980

212.

Onwubolu GC (2006b) Performance-based optimization of multi-pass face milling operations using tribes. Int J Mach Tools Manuf 46:717–727

213.

Onwubolu GC (2009) Prediction of burr formation during face milling using a hybrid GMDH network model with optimized cutting conditions. Int J Adv Manuf Technol 44(11–12):1083–1093

214.

Onwubolu GC, Clerc M (2004) Optimal path for automated drilling operations by a new heuristic approach using particle swarm optimization. Int J Prod Res 42(3):473–491

MATH215.

Onwubolu GC, Kumalo T (2001a) Optimization of multipass turning operations with genetic algorithms. Int J Prod Res 39(16):3727–3745

MATH216.

Onwubolu GC, Kumalo T (2001b) Multi-pass turning operations optimization based on genetic algorithms. Proc Inst Mech Eng Part B J Eng Manuf 215:117–124

217.

Onwubolu GC, Kumar S (2006) Response surface methodology-based approach to CNC drilling operations. J Mater Process Technol 171(1):41–47

218.

Onwubolu GC, Buryan P, Lemke F (2008) Modeling tool wear in end-milling using enhanced GMDH learning networks. Int J Adv Manuf Technol 39(11–12):1080–1092

219.

Ozcelik B, Bağci E (2006) Experimental and numerical studies on the determination of twist drill temperature in dry drilling: a new approach. Mater Des 27(10):920–927

220.

Ozcelik B, Oktem H, Kurtaran H (2005) Optimum surface roughness in end milling Inconel 718 by coupling neural network model and genetic algorithm. Int J Adv Manuf Technol 27(3–4):234–241

221.

Pa PS (2007) Design of freeform surface finish using burnishing assistance following electrochemical finishing. J Mech Sci Technol 21(10):1630–1636

222.

Paiva AP, Ferreira JR, Balestrassi PP (2007) A multivariate hybrid approach applied to AISI 52100 hardened steel turning optimization. J Mater Process Technol 189(1–3):26–35

223.

Pal SK, Chakraborty D (2005) Surface roughness prediction in turning using artificial neural network. Neural Comput Appl 14:319–324

224.

Palanisamy P, Rajendran I, Shanmugasundaram S (2007) Optimization of machining parameters using genetic algorithm and experimental validation for end-milling operations. Int J Adv Manuf Technol 32(7–8):644–655

225.

Panda SS, Chakraborty D, Pal SK (2008) Flank wear prediction in drilling using back propagation neural network and radial basis function network. App Soft Comput 8(2):858–871

226.

Park HW, Liang SY (2008) Force modeling of micro-grinding incorporating crystallographic effects. Int J Mach Tools Manuf 48(15):1658–1667

227.

Patel K, Batish A, Bhattacharya A (2009) Optimization of surface roughness in an end-milling operation using nested experimental design. Prod Eng 3(4–5):361–373

228.

Paul A, Kapoor SG, DeVor RE (2005) Chisel edge and cutting lip shape optimization for improved twist drill point design. Int J Mach Tools Manuf 45(4–5):421–431

229.

Pedersen NL (2004) Optimization of holes in plates for control of eigenfrequencies. Struct Multi Optim 28(1):1–10

230.

Prakash S, Palanikumar K, Manoharan N (2009) Optimization of delamination factor in drilling medium-density fiberboards (MDF) using desirability-based approach. Int J Adv Manuf Technol 45(3–4):370–381

231.

Prakasvudhisarn C, Kunnapapdeelert S, Yenradee P (2009) Optimal cutting condition determination for desired surface roughness in end milling. Int J Adv Manuf Technol 41(5–6):440–451

232.

Prasad AVS, Rao RK, Rao VKS (1997) Optimal selection of process parameter for turning operation in CAPP system. Int J Prod Res 35(6):1495–1522

MATH233.

Quiza R, Figueira L, Davim JP (2008) Comparing statistical models and artificial neural networks on predicting the tool wear in hard machining D2 AISI steel. Int J Adv Manuf Technol 37:641–648

234.

Radhakrishnan T, Nandan U (2005) Milling force prediction using regression and neural networks. J Intell Manuf 16(1):93–102

235.

Rai JK, Xirouchakis P (2008) Finite element method based machining simulation environment for analyzing part errors induced during milling of thin-walled components. Int J Mach Tools Manuf 48(6):629–643

236.

Rajemi MF, Mativenga PT, Aramcharoen A (2010) Sustainable machining: selection of optimum turning conditions based on minimum energy considerations. J Cleaner Prod 18(10–11):1059–1065

237.

Rao RV, Pawar PJ (2010a) Parameter optimization of a multi-pass milling process using non-traditional optimization algorithms. Appl Soft Comp 10(2):445–456

238.

Rao RV, Pawar PJ (2010b) Grinding process parameter optimization using non-traditional optimization algorithms. Proc Inst Mech Eng Part B J Eng Manuf. doi:

10.1243/09544054JEM1782
239.

Rao DS, Hebbar HS, Komaraiah M (2007) Surface hardening of high-strength low alloy steels (hsla) dual-phase steels by ball burnishing using factorial design. Mater Manuf Process 22(7):825–829

240.

Rao DS, Hebbar HS, Komaraiah M, Kempaiah UN (2008) Investigations on the effect of ball burnishing parameters on surface hardness and wear resistance of HSLA dual-phase steels. Mater Manuf Process 23(3):295–302

241.

Rawat S, Attia H (2009) Wear mechanisms and tool life management of WC–Co drills during dry high speed drilling of woven carbon fibre composites. Wear 267(5–8):1022–1030

242.

Reddy NSK, Rao PV (2005) Selection of optimum tool geometry and cutting conditions using a surface roughness prediction model for end milling. Int J Adv Manuf Technol 26(11–12):1202–1210

243.

Reddy NSK, Rao PV (2006) Selection of an optimal parametric combination for achieving a better surface finish in dry milling using genetic algorithms. Int J Adv Manuf Technol 28(5–6):463–473

244.

Reddy SVB, Shunmugam MS, Narendran TT (1998) Optimal sub-division of the depth of cut to achieve minimum production cost in multi-pass turning using a genetic algorithm. J Mater Process Technol 79(1–3):101–108

245.

Routara BC, Bandyopadhyay A, Sahoo P (2009) Roughness modeling and optimization in CNC end milling using response surface method: effect of workpiece material variation. Int J Adv Manuf Technol 40(11–12):1166–1180

246.

Rowe WB, Yan L, Inasaki I, Malkin S (1994) Application of artificial intelligence in grinding. CIRP Ann Manuf Technol 43(2):521–531

247.

Rowe WB, Li Y, Mills B, Allanson DR (1996) Application of intelligent CNC in grinding. Comput Ind 31(1):45–60

248.

Rowe WB, Li Y, Chen X, Mills B (1997) An intelligent multiagent approach for selection of grinding conditions. CIRP Ann Manuf Technol 46(1):233–238

249.

Roy SS (2006) Design of genetic-fuzzy expert system for predicting surface finish in ultra-precision diamond turning of metal matrix composite. J Mater Process Technol 173(3):337–344

250.

Saljé E, See MV (1987) Process-Optimization in Honing. CIRP Ann Manuf Technol 36(1):235–239

251.

Samhouri MS, Surgenor BW (2005) Surface roughness in grinding: on-line prediction with adaptive neuro-fuzzy inference system. Trans NAMRI/SME 33:57–64

252.

Sanjay C, Jyothi C (2006) A study of surface roughness in drilling using mathematical analysis and neural networks. Int J Adv Manuf Technol 29(9–10):846–852

253.

Sanjay C, Neema ML, Chin CW (2005) Modeling of tool wear in drilling by statistical analysis and neural network. J Mater Process Technol 170:494–500

254.

Saravanan R, Sachithanandam M (2001) Genetic algorithm (GA) for multivariable surface grinding process optimization using a multi-objective function model. Int J Adv Manuf Technol 17:330–338

255.

Saravanan R, Ashokan P, Sachithanandam M (2001) Comparative analysis of conventional and non-conventional optimization technique for CNC-turning process. Int J Adv Manuf Technol 17:471–476

256.

Saravanan R, Asokan P, Sachidanandam M (2002) A multi-objective genetic algorithm (GA) approach for optimization of surface grinding operations. Int J Mach Tools Manuf 42(12):1327–1334

257.

Saravanan R, Sankar RS, Asokan P, Vijayakumar K, Prabhaharan G (2005) Optimization of cutting conditions during continuous finished profile machining using non-traditional techniques. Int J Adv Manuf Technol 26(1–2):30–40

258.

Sardiñas RQ, Reis P, Davim JP (2006a) Multi-objective optimization of cutting parameters for drilling laminate composite materials by using genetic algorithms. Compos Sci Technol 66(15):3083–3088

259.

Sardiñas RQ, Santana MR, Brindis EAA (2006b) Genetic algorithm-based multi-objective optimization of cutting parameters in turning processes. Eng Appl Artif Intell 19(2):127–133

260.

Sathyanarayanan G, Lin IJ, Chen MK (1992) Neural network modeling and multiobjective optimization of creep feed grinding of superalloys. Int J Prod Res 30(10):2421–2438

261.

Satishkumar S, Asokan P, Kumanan S (2006) Optimization of depth of cut in multi-pass turning using nontraditional optimization techniques. Int J Adv Manuf Technol 29(3–4):230–238

262.

Savas V, Ozay C (2008) The optimization of the surface roughness in the process of tangential turn-milling using genetic algorithm. Int J Adv Manuf Technol 37(3–4):335–340

263.

Sedighi M, Afshari D (2009) Creep feed grinding optimization by an integrated GA-NN system. J Intell Manuf. doi:

10.1007/s10845-009-0243-4
264.

Shaji S, Radhakrishnan V (2003) Analysis of process parameters in surface grinding with graphite as lubricant based on the Taguchi method. J Mater Process Technol 141(1):51–59

265.

Sharma VS, Dhiman S, Sehgal R, Sharma SK (2008) Estimation of cutting forces and surface roughness for hard turning using neural networks. Int J Adv Manuf Technol 19(4):473–483

266.

Sheng Y, Tomizuka M (2006) Intelligent modeling of thrust force in drilling process. J Dyn Syst Meas Control 128(4):846–856

267.

Shin YC, Joo YS (1992) Optimization of machining conditions with practical constraints. Int J Prod Res 30(12):2907–2919

268.

Shiou FJ, Chen CH (2003) Freeform surface finish of plastic injection mold by using ball-burnishing process. J Mater Process Technol 140(1–3):248–254

269.

Shiou FJ, Cheng CH (2008) Ultra-precision surface finish of NAK80 mould tool steel using sequential ball burnishing and ball polishing processes. J Mater Process Technol 201(1–3):554–559

270.

Shiou FJ, Ciou HS (2008) Ultra-precision surface finish of the hardened stainless mold steel using vibration-assisted ball polishing process. Int J Mach Tools Manuf 48(7–8):721–732

271.

Shiou FJ, Hsu CC (2008) Surface finishing of hardened and tempered stainless tool steel using sequential ball grinding, ball burnishing and ball polishing processes on a machining centre. J Mater Process Technol 205(1–3):249–258

272.

Shunmugam MS, Reddy SVB, Narendran AA (2000a) Selection of optimal conditions in multi-pass face-milling using a genetic algorithm. Int J Mach Tools Manuf 40:401–414

273.

Shunmugam MS, Reddy SVB, Narendran TT (2000b) Optimal selection of parameters in multi-tool drilling. J Mater Process Technol 103(2):318–323

274.

Sick B (2002) On-line and indirect tool wear monitoring in turning with artificial neural net works: a review of more than a decade of research. Mech Syst Signal Process 16(4):487–546

275.

Siddiquee AN, Khan ZA, Mallick Z (2010) Grey relational analysis coupled with principal component analysis for optimization design of the process parameters in in-feed centreless cylindrical grinding. Int J Adv Manuf Technol 46(9–12):983–992

276.

Singh I, Bhatnagar N, Viswanath P (2008) Drilling of uni-directional glass fiber reinforced plastics: experimental and finite element study. Mater Des 29(2):546–553

277.

Sonar DK, Dixit US, Ojha DK (2006) The application of radial basis function neural network for predicting the surface roughness in a turning process. Int J Adv Manuf Technol 27(7–8):661–666

278.

Sonmez AI, Baykasoglu A, Dereli T, Filiz IH (1999) Dynamic optimization of multipass milling operations via geometric programming. Int J Mach Tools Manuf 39:297–332

279.

Soodamani R, Liu ZQ (2000) GA-based learning for a model-based object recognition system. Int J Approx Reas 23(2):85–109

MATH280.

Sreeram S, Kumar AS, Rahman M, Zaman MT (2006) Optimization of cutting parameters in micro end milling operations in dry cutting condition using genetic algorithms. Int J Adv Manuf Technol 30(11–12):1030–1039

281.

Srinivas J, Giri R, Yang SH (2009) Optimization of multi-pass turning using particle swarm intelligence. Int J Adv Manuf Technol 40(1–2):56–66

282.

Stępień P (2009) A probabilistic model of the grinding process. Appl Math Modell 33(10):3863–3884

MATH283.

Stone R, Krishnamurthy K (1996) A neural network thrust force controller to minimize delaminating during drilling of graphite—epoxy laminates. Int J Mach Tools Manuf 36:985–1003

284.

Suresh PVS, Rao PV, Deshmukh SG (2002) A genetic algorithmic approach for optimization of surface roughness prediction model. Int J Mach Tools Manuf 42(6):675–680

285.

Tan FP, Creese RC (1995) A generalized multi-pass machining model for machining parameter selection in turning. Int J Prod Res 33(5):1467–1487

MATH286.

Tandon V, El-Mounayri H, Kishawy H (2002) NC end milling optimization using evolutionary computation. Int J Mach Tools Manuf 42(5):595–605

287.

Tang Y (2006) Optimization strategy in end milling process for high speed machining of hardened die/mold steel. J Univ Sci Technol Beijing Miner Metall Mater 13(3):240–243

288.

Tolouei-Rad M, Bidhendi IM (1997) On the optimization of machining parameters for milling operations. Int J Mach Tools Manuf 37:1–16

289.

Tönshoff HK, Peters J, Inasaki I, Paul T (1992) Modeling and simulation of grinding processes. CIRP Ann Manuf Technol 41(2):677–688

290.

Totis G (2009) RCPM: a new method for robust chatter prediction in milling. Int J Mach Tools Manuf 49(3–4):273–284

291.

Trmal GJ, Zhu CB, Midha PS (1992) An expert system for grinding process optimization. J Mater Process Technol 33(4):507–517

292.

Tsao CC (2007) Taguchi analysis of drilling quality associated with core drill in drilling of composite material. Int J Adv Manuf Technol 32(9–10):877–884

293.

Tsao CC, Hocheng H (2004) Taguchi analysis of delamination associated with various drill bits in drilling of composite material. Int J Mach Tools Manuf 44(10):1085–1090

294.

Tsao CC, Hocheng H (2008) Evaluation of thrust force and surface roughness in drilling composite material using Taguchi analysis and neural network. J Mater Process Technol 203(1–3):342–348

295.

Tzeng YF (2006) Parameter design optimization of computerised numerical control turning tool steels for high dimensional precision and accuracy. Mater Des 27(8):665–675

296.

Tzeng CJ, Lin YH, Yang YK, Jeng MC (2009) Optimization of turning operations with multiple performance characteristics using the Taguchi method and Grey relational analysis. J Mater Process Technol 209(6):2753–2759

297.

Umbrello D, Ambrogio G, Filice L, Shivpuri R (2008) A hybrid finite element method: artificial neural network approach for predicting residual stresses and the optimal cutting conditions during hard turning of AISI 52100 bearing steel. Mater Des 29(4):873–883

298.

Uros Z, Franc C, Edi K (2009) Adaptive network based inference system for estimation of flank wear in end-milling. J Mater Process Technol 209(3):1504–1511

299.

Varghese B, Malkin S (1998) Experimental investigation of methods to enhance stock removal for superfinishing. CIRP Ann Manuf Technol 47(1):231–234

300.

Varghese B, Malkin S (2000) Selection of optimal superfinishing parameters. J Manuf Process 2(2):124–130

301.

Venk S, Govind R, Merchant ME (1990) An expert system approach to optimization of the centerless grinding process. CIRP Ann Manuf Technol 39(1):489–492

302.

Vijayakumar K, Prabhaharan G, Asokan P, Saravanan R (2003) Optimization of multi-pass turning operations using ant colony system. Int J Mach Tools Manuf 43(15):1633–1639

303.

Vinolas J, Biera J, Nieto J, Llorente JI, Vigneau J (1997) the use of an efficient and intuitive tool for the dynamic modeling of grinding processes. CIRP Ann Manuf Technol 46(1):239–242

304.

Wan M, Zhang WH, Tan G, Qin GH (2008) Systematic simulation procedure of peripheral milling process of thin-walled workpiece. J Mater Process Technol 197(1–3):122–131

305.

Wang J (1993) Multiple objective optimization of machining operations based on neural networks. Int J Adv Manuf Technol 8:235–243

306.

Wang J (1998) Computer-aided economic optimization of end-milling operations. Int J Prod Econ 54(3):307–320

307.

Wang YC (2007) A note on ‘optimization of multi-pass turning operations using ant colony system’. Int J Mach Tools Manuf 47(12–13):2057–2059

308.

Wang DX, Zuo MJ, Qi KZ, Liang M (1996) Online tool adjustment with adaptive tool wear function identification. Int J Prod Res 34(9):2499–2515

MATH309.

Wang J, Zhang B, Xue B (2000) Computer-controlled lapping system for granite surface plates. J Manuf Syst 19(3):149–155

310.

Wang X, Da ZJ, Balaji AK, Jawahir IS (2002) Performance-based optimal selection of cutting conditions and cutting tools in multi-pass turning operations using genetic algorithms. Int J Prod Res 40(9):2053–2065

MATH311.

Wang ZG, Rahman M, Wong YS, Sun J (2005) Optimization of multi-pass milling using parallel genetic algorithm and parallel genetic simulated annealing. Int J Mach Tools Manuf 45:1726–1734

312.

Wang X, Da ZJ, Balaji AK, Jawahir IS (2007) Performance-based predictive models and optimization methods for turning operations and applications: part 3-optimum cutting conditions and selection of cutting tools. J Manuf Processes 9(1):61–74

313.

Wei ZC, Wang MJ, Ma RG, Wang L (2010) Modeling of process geometry in peripheral milling of curved surfaces. J Mater Process Technol 210(5):799–806

314.

Weinert K, Blum H, Jansen T, Rademacher A (2007) Simulation based optimization of the NC-shape grinding process with toroid grinding wheels. Prod Eng 1(3):245–252

315.

Wen XM, Tay AAO, Nee AYC (1992) Micro-computer-based optimization of the surface grinding process. J Mater Process Technol 29(1–3):75–90

316.

Xiao G, Malkin S (1996) On-line optimization for internal plunge grinding. CIRP Ann Manuf Technol 45(1):287–292

317.

Xu W, Wu Y, Sato T, Lin W (2010) Effects of process parameters on workpiece roundness in tangential-feed centerless grinding using a surface grinder. J Mater Process Technol 210(5):759–766

318.

Yang WH, Tarng YS (1998) Design optimization of cutting parameters for turning operations based on the Taguchi method. J Mater Process Technol 84:122–129

319.

Yang YK, Chuang MT, Lin SS (2009) Optimization of dry machining parameters for high-purity graphite in end milling process via design of experiments methods. J Mater Process Technol 209(9):4395–4400

320.

Yao Y, Zhao H, Li J, Yuan Z (2006) Modeling of virtual workpiece with machining errors representation in turning. J Mater Process Technol 172(3):437–444

321.

Yildiz AR (2009a) An effective hybrid immune-hill climbing optimization approach for solving design and manufacturing optimization problems in industry. J Mater Process Technol 209(6):2773–2780

322.

Yildiz AR (2009b) A novel hybrid immune algorithm for optimization of machining parameters in milling operations. Robot Comput Integr Manuf 25(2):261–270

323.

Yildiz AR, Ozturk F (2006) Hybrid enhanced genetic algorithm to select optimal machining parameters in turning operation. Proc Inst Mech Eng Part B J Eng Manuf 220(12):2041–2053

324.

Zarei O, Fesanghary M, Farshi B, Saffar RJ, Razfar MR (2009) Optimization of multipass face-milling via harmony search algorithm. J Mater Process Technol 209:2386–2392

325.

Zhang JZ, Chen JC (2009) Surface roughness optimization in a drilling operation using the taguchi design method. Mater Manuf Processes 24(4):459–467

326.

Zhang LB, Wang LJ, Liu XY, Zhao HW, Wang X, Luo HY (2001) Mechanical model for predicting thrust and torque in vibration drilling fibre-reinforced composite materials. Int J Mach Tools Manuf 41(5):641–657

MATH327.

Zhang C, Rentsch R, Brinksmeier E (2005) Advances in micro ultrasonic assisted lapping of microstructures in hard–brittle materials: a brief review and outlook. Int J Mach Tools Manuf 45(7–8):881–890

328.

Zheng HQ, Li XP, Wong YS, Nee AYC (1999) Theoretical modeling and simulation of cutting forces in face milling with cutter runout. Int J Mach Tools Manuf 39(12):2003–2018

329.

Zhu GY, Zhang WB (2008) Drilling path optimization by the particle swarm optimization algorithm with global convergence characteristics. Int J Prod Res 46:2299–2311

MATH330.

Zhu CB, Midha PS, Trmal GJ (1993) A dynamic modeling approach to computer aided optimum selection of grinding parameters. J Mater Process Technol 38(1–2):227–245

331.

Zolgharni M, Jones BJ, Bulpett R, Anson AW, Fanks J (2008) Energy efficiency improvements in dry drilling with optimised diamond-like carbon coatings. Diam Rel Mater 17(7–10):1733–1737

332.

Zuperl U, Cus F (2003) Optimization of cutting conditions during cutting by using neural networks. Robot Comput Integr Manuf 19(1–2):189–199