Tool condition monitoring in the milling process with vegetable based cutting fluids using vibration signatures

References

1 M. H.Cetin, B.Ozcelik, E.Kuram, E.Demirbas: Evaluation of vegetable based cutting fluids with extreme pressure and cutting parameters in turning of AISI 304L by Taguchi method, Journal of Cleaner Production19 (2011), No. 17, pp. 2049–205610.1016/j.jclepro.2011.07.013.Search in Google Scholar

2 S.Debnath, M. M.Reddy, Q. S.Yi: Influence of cutting fluid conditions and cutting parameters on surface roughness and tool wear in turning process using Taguchi method, Measurement78 (2016), pp. 111–11910.1016/j.measurement.2015.09.011.Search in Google Scholar

3 M. S. H.Bhuiyan, I. A.Choudhury: Investigation of Tool Wear and Surface Finish by Analyzing Vibration Signals in Turning Assab-705 Steel, Machining Science and Technology19 (2015), No. 2, pp. 236–26110.1080/10910 344.2015.1018531.Search in Google Scholar

4 M. A.Xavior, M.Adithan: Determining the influence of cutting fluids on tool wear and surface roughness during turning of AISI 304 austenitic stainless steel, Journal of materials processing technology209 (2009), No. 2, pp. 900–90910.1016/j.jmatprotec.2008.02.068.Search in Google Scholar

5 S. M.Alves, J. F. G.de Oliveira: Development of new cutting fluid for grinding process adjusting mechanical performance and environmental impact, Journal of materials processing technology179 (2006), No. 1, pp. 185–18910.1016/j.jmatprotec.2006.03.090.Search in Google Scholar

6 B.Ozcelik, E.Kuram, M. H.Cetin, E.Demirbas: Experimental investigations of vegetable based cutting fluids with extreme pressure during turning of AISI 304L, Tribology International44 (2011), No. 12, pp. 1864–187110.1016/j.triboint.2011.07.012.Search in Google Scholar

7 W.Belluco and L.De Chiffre: Performance evaluation of vegetable-based oils in drilling austenitic stainless steel, Journal of Materials Processing Technology148 (2004), No. 2, pp. 171–17610.1016/S0924-0136(03)00679-4.Search in Google Scholar

8 S. A.Lawal, I. A.Choudhury, Y.Nukman: Evaluation of vegetable and mineral oil-in-water emulsion cutting fluids in turning AISI 4340 steel with coated carbide tools, Journal of Cleaner Production66 (2014), No. pp. 610–61810.1016/j.jclepro.2013.11.066.Search in Google Scholar

9 S.Ojolo, M.Amuda, O.Ogunmola, C.Ononiwu: Experimental determination of the effect of some straight biological oils on cutting force during cylindrical turning, Matéria (Rio de Janeiro)13 (2008), No. 4, pp. 650–66310.1590/S1517-70762008000400011Search in Google Scholar

10 S.Shankar, T.Mohanraj: Tool condition monitoring in milling using sensor fusion technique, Proc. of the Malaysian International Tribology Conference 2015, Malaysian Tribology Society, Malaysia (2015), pp. 322–323Search in Google Scholar

11 X.Shi, R.Wang, Q.Chen, H.Shao: Cutting sound signal processing for tool breakage detection in face milling based on empirical mode decomposition and independent component analysis, Journal of Vibration and Control21 (2014), No. 16, pp. 107754631452282610.1177/1077546314522826.Search in Google Scholar

12 P.Kanakarajan, S.Sundaram, A.Kumaravel, R.Rajasekar, R.Venkatachalam: Acoustic emission testing of the machining performance of SiC grinding wheel shaped Al2O3 ceramics, Materials Testing58 (2016), No. 10, pp. 908–91210.3139/120.110938.Search in Google Scholar

13 P.Kanakarajan, S.Sundaram, A.Kumaravel, R.Rajasekar, P. S.Kumar: Acoustic emission testing of surface roughness and wear caused by grinding of ceramic materials, Materials Testing57 (2015), No. 4, pp. 337–34210.313/120.110714.Search in Google Scholar

14 S.Shankar, S. K.Thangarasu, T.Mohanraj, D.Pravien: Prediction of cutting force in turning process: An experimental and fuzzy approach, Journal of Intelligent & Fuzzy Systems28 (2015), No. 4, pp. 1785–179310.3233/IFS-141465.Search in Google Scholar

15 W.Rmili, A.Ouahabi, R.Serra, R.Leroy: An automatic system based on vibratory analysis for cutting tool wear monitoring, Measurement77 (2016), pp. 117–12310.1016/j.measurement.2015.09.010.Search in Google Scholar

16 D.Salgado, F.Alonso: Tool wear detection in turning operations using singular spectrum analysis, Journal of Materials Processing Technology171 (2006), No. 3, pp. 451–45810.1016/j.jmatprotec.2005.08.005.Search in Google Scholar

17 C.Aliustaoglu, H. M.Ertunc, H.Ocak: Tool wear condition monitoring using a sensor fusion model based on fuzzy inference system, Mechanical Systems and Signal Processing23 (2009), No. 2, pp. 539–54610.1016/j.ymssp.2008.02.010.Search in Google Scholar

18 N.Mehta, P.Pandey, G.Chakravarti: An investigation of tool wear and the vibration spectrum in milling, Wear91 (1983), No. 2, pp. 219–23410.1016/0043-1648(83)90256-9.Search in Google Scholar

19 I.Yesilyurt, H.Ozturk: Tool condition monitoring in milling using vibration analysis, International Journal of Production Research45 (2007), No. 4, pp. 1013–102810.1080/00207540600677781.Search in Google Scholar

20 S.Orhan, A. O.Er, N.Camuşcu, E.Aslan: Tool wear evaluation by vibration analysis during end milling of AISI D3 cold work tool steel with 35 HRC hardness, NDT & E International40 (2007), No. 2, pp. 121–12610.1016/j.ndteint.2006.09.006.Search in Google Scholar

21 H.Chelladurai, V.Jain, N.Vyas: Development of a cutting tool condition monitoring system for high speed turning operation by vibration and strain analysis, The International Journal of Advanced Manufacturing Technology37 (2008), No. 5–6, pp. 471–48510.1007/s00170-007-0986-z.Search in Google Scholar

22 J. C.Chen, W. L.Chen: A tool breakage detection system using an accelerometer sensor, Journal of Intelligent Manufacturing10 (1999), No. 2, pp. 187–19710.1023/A:1008980821787.Search in Google Scholar

23 X.Li: Real-time tool wear condition monitoring in turning, International Journal of Production Research39 (2001), No. 5, pp. 981–99210.1080/00207540 010005745.Search in Google Scholar

24 G.Vetrichelvan, S.Sundaram, S. S.Kumaran, P.Velmurugan: An investigation of tool wear using acoustic emission and genetic algorithm, Journal of Vibration and Control21 (2015), No. 15, pp. 3061–306610.1177/10775 46314520835.Search in Google Scholar

25 P.Bhattacharyya, D.Sengupta, S.Mukhopadhyay, A.Chattopadhyay: On-line tool condition monitoring in face milling using current and power signals, International Journal of Production Research46 (2008), No. 4, pp. 1187–120110.1080/00207540600940288.Search in Google Scholar

26 W.Wang, G.Hong, Y.Wong, K.Zhu: Sensor fusion for online tool condition monitoring in milling, International Journal of Production Research45 (2007), No. 21, pp. 5095–511610.1080/00207540500536913.Search in Google Scholar

27 S.Cho, S.Binsaeid, S.Asfour: Design of multisensor fusion-based tool condition monitoring system in end milling, The International Journal of Advanced Manufacturing Technology46 (2010), No. 5–8, pp. 68–69410.1007/s00170-009-2110-z.Search in Google Scholar

28 A.Uysal: Cutting parameters for optimum surface roughness during end milling of carbon fiber reinforced composites, Materials Testing58 (2016), No. 6, pp. 588–59310.3139/120.110881.Search in Google Scholar

29 S.Shankar, T.Mohanraj, S. K.Thangarasu: Multi-response milling process optimization using the Taguchi method coupled to grey relational analysis, Materials Testing58 (2016), No. 5, pp. 462–47010.3139/120.110869.Search in Google Scholar

30 M.Lamraoui, M.Barakat, M.Thomas, M. ElBadaoui: Chatter detection in milling machines by neural network classification and feature selection, Journal of Vibration and Control21 (2015), No. 7, pp. 1251–126610.1177/10775463 13493919.Search in Google Scholar

31 T.Kıvak, Ş.Mert: Application of the Taguchi technique for the optimization of surface roughness and tool life during the milling of Hastelloy C22, Materials Testing59 (2017), No. 1, pp. 697610.3139/120.110967.Search in Google Scholar