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Optimization of design for the high precision end mill spindles to improve stability of effective cutting process

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Abstract

This paper presents an optimum design approach of spindle-tool system for improvising the dynamic stability of cutting process. Prediction of dynamic behaviour at the tool tip is necessary in assessing the machining stability of a machine tool during design stage. Spindle-tool assembly is initially analysed by using finite element analysis with Timoshenko beam elements and tool-tip frequency response functions are obtained. In order to maximize the chatter-free region in the stability lobe diagram, an optimization study is carried-out by considering spindle parameters such as bearing locations on spindle shaft along with tool-overhang as design variables. A simulated experimental dynamic data consisting of natural frequencies and average stable depth of cut is obtained for different combinations of tool overhang and bearing span values. Based on the obtained results, the data is generalized using a feed-forward neural network model which is employed to estimate the average stable depths for the optimization module. A global meta-heuristic optimization scheme namely genetic algorithm is employed to achieve the spindle design data corresponding to maximum average stable depth of cut and it is validated with. End-milling experiments are carried-out to validate the stability states corresponding to various axial depths of cut.

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References

  1. Altintas, Y., Budak, E.: Analytical prediction of stability lobes in milling. Ann. CIRP 44, 357–362 (1995)

    Article  Google Scholar 

  2. Altintas, Y., Weck, M.: Chatter Stability of Metal Cutting and Grinding. CIRP Ann. Manf. Tech. 53, 619–642 (2004)

    Article  Google Scholar 

  3. Bravo, U., Altuzarra, O., Lopez de Lacalle, L.N., Sanchez, J.A., Campa, F.J.: Stability limits of milling considering the flexibility of the workpiece and the machine. Int. J. Mach. Tools Manf. 45, 1669–1680 (2005)

    Article  Google Scholar 

  4. Gagnola, V., Bouzgarrou, B.C., Raya, P., Barra, C.: Model-based chatter stability prediction for high-speed spindles. Int. J. Mach. Tools Manf. 47, 1176–1186 (2007)

    Article  Google Scholar 

  5. Tanga, W.X., Songa, Q.H.: Prediction of chatter stability in high-speed finishing end Milling considering multi-mode dynamics. Int. J. Mach. Tools Manf. 209, 2585–2591 (2009)

    Google Scholar 

  6. Suzuki, N., Kurata, Y., Kato, T., Hino, R., Shamoto, E.: Identification of transfer function by inverse analysis of self-excited chatter vibration in milling operations. Precis. Eng. 36, 568–575 (2012)

    Article  Google Scholar 

  7. Raphael, G.S., Reginaldo, T.C.: A Contribution to improve the accuracy of chatter prediction in machine tools using the stability lobe diagram. J. Manf. Sci. Eng. ASME 136, 021005–021007 (2014)

    Article  Google Scholar 

  8. Lin, C.W., Tu, J.F.: Model-based design of motorized spindle systems to improve dynamic performance at high speeds. J. Manuf. Process. 9, 94–108 (2007)

    Article  Google Scholar 

  9. Jiang, S., Zheng, S.: Dynamic design of a high-speed motorized spindle-bearing system. J. Mech. Des. ASME 132, 0345011–0345015 (2010)

    Article  Google Scholar 

  10. Penga, Z.K., Jackson, M.R., Guo, L.Z., Parkin, R.M., Meng, G.: Effects of bearing clearance on the chatter stability of milling process. Nonlinear Anal. Real World Appl. 11, 3577–3589 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  11. Cao, H., Holkup, T., Altintas, Y.: A comparative study on the dynamics of high speed spindles with respect to different preload mechanisms. Int. J. Mach. Tools Manf 57, 871–883 (2011)

    Google Scholar 

  12. Gao, S.H., Meng, G.: Research of the spindle over hang and bearing span on the system milling stability. Arch. Appl. Mech. 81, 1473–1486 (2011)

    Article  MATH  Google Scholar 

  13. Ozturk, E., Kumar, U., Turner, S., Schmitz, T.: Investigation of spindle bearing preload on dynamics and stability limit in milling. Int. J. Mach. Tools Manf. 61, 343–346 (2012)

    Google Scholar 

  14. Liu, J., Chen, X.: Dynamic design for motorized spindles based on an integrated model. Int. J. Adv. Manuf. Technol. 71, 1961–1974 (2014)

    Article  Google Scholar 

  15. Altintas, Y.: Modeling Approaches and software for predicting the performance of milling operations at Mal-Ubc. Mach. Sci. Technol. Int. J. 4, 3445–3478 (2000)

    Google Scholar 

  16. Jalalli Saffar, R., Razfar, M.R.: Simulation of end milling operation for predicting cutting forces to minimize tool deflection by genetic algorithm. Mach. Sci. Technol. Int. J. 14, 81–101 (2010)

    Article  Google Scholar 

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

    Article  Google Scholar 

  18. Hsieh, H.T., Chu, C.H.: Improving optimization of tool path planning in 5-axis flank milling using advanced PSO algorithms. Robot. Comput. Integrated Manuf. 29, 3–11 (2013)

    Article  Google Scholar 

  19. Zareia, O., Fesanghary, M., Farshi, B., Saffar, J., Razfar, R.M.R.: Optimization of multi-pass face-milling via harmony search algorithm. J. Mater. Process. Technol. 209, 2386–2392 (2009)

    Article  Google Scholar 

  20. Wang, D., Penter, L., Hänel, A., Steffen, I., Marian, W.: Stability enhancement and chatter suppression in continuous radial immersion milling. Int. J. Mech. Sci. 235, 107711 (2022)

    Article  Google Scholar 

  21. Florian, W., Jim, B., Petra, W.: A systematic approach for data acquisition and analysis of spindle speed-dependent modal parameters. Proc. CIRP 118, 205–210 (2023)

    Article  Google Scholar 

  22. Kaidong, C., He, Z., Nathan, V., Emmanuel, D.: An alternative approach to model the dynamics of a milling tool. J. Sound Vib. 569(20), 117940 (2023)

    Google Scholar 

  23. Cheepu, M., Baek, H.J., Kim, Y.S., Cho, S.M., Melting characteristics of C-type filler metal in GTAW. Weld. J. 102(9), 201–216 (2023). https://doi.org/10.29391/2023.102.016

  24. Cheepu, M., Susila, P.: Growth rate of intermetallics in aluminum to copper dissimilar welding. Trans. Indian Inst. Met. 73, 1509–1514 (2020). https://doi.org/10.1007/s12666-020-01905-z

    Article  Google Scholar 

  25. Muralimohan, C.H., Haribabu, S., Reddy, Y.H., Muthupandi, V., Sivaprasad, K.: Evaluation of microstructures and mechanical properties of dissimilar materials by friction welding. Proc. Mater. Sci. 5, 1107–1113 (2014)

    Article  Google Scholar 

  26. Cho, D.-W., Park, Y.-D., Cheepu, M.: Numerical simulation of slag movement from marangoni flow for GMAW with computational fluid dynamics. Int. Commun. Heat Mass Transf. 125, 105243 (2021)

    Article  Google Scholar 

  27. Cheepu, M., Cheepu, H., Karpagaraj, A., Che, W.S.: Influence of joint interface on mechanical properties in dissimilar friction welds. Adv. Mater. Process. Technol. 8(1), 732–744 (2022). https://doi.org/10.1080/2374068X.2020.1832413

    Article  Google Scholar 

  28. Park, J.H., Cheepu, M., Cho, S.M.: Analysis and Characterization of the weld pool and bead geometry of inconel 625 super-TIG welds. Metals 10, 365 (2020). https://doi.org/10.3390/met10030365

    Article  Google Scholar 

  29. Anuradha, M., Das, V.C., Susila, P., et al.: Effect of welding parameters on TIG welding of inconel 718 to AISI 4140 steel. Trans. Indian Inst. Met. 73, 1515–1520 (2020). https://doi.org/10.1007/s12666-020-01926-8

    Article  Google Scholar 

  30. Cheepu, M., Che, W.S.: Friction welding of titanium to stainless steel using Al interlayer. Trans. Indian Inst. Met. 72, 1563–1568 (2019). https://doi.org/10.1007/s12666-019-01655-7

    Article  Google Scholar 

  31. Cheepu, M., Baek, H.J., Kim, Y.S., Cho, S.M.: Penetration estimation of GTAW with C-type filler by net heat input ratio. Weld. J. 101, 240s–248s (2022)

    Article  Google Scholar 

  32. Cheepu, M.: Machine learning approach for the prediction of defect characteristics in wire arc additive manufacturing. Trans. Indian Inst. Met. 76, 447–455 (2023). https://doi.org/10.1007/s12666-022-02715-1

    Article  Google Scholar 

  33. Ainapurapu, S.B., Devulapalli, V.A., Theagarajan, R.P., Chigilipalli, B.K., Kottala, R.K., Cheepu, M.: Microstructure and mechanical properties of the bimetallic wire arc additively manufactured structure (BAMS) of SS304L and SS308L fabricated by hybrid manufacturing process. Trans. Indian Inst. Met. 76(2), 419–426 (2023)

    Article  Google Scholar 

  34. Kumar, K.R., Balasubramanian, K.R., Kumar, G.P., Bharat Kumar, C., Cheepu, M.M.: Experimental investigation of nano-encapsulated molten salt for medium-temperature thermal storage systems and modeling of neural networks. Int. J. Thermophys. 43(9), 145 (2022). https://doi.org/10.1007/s10765-022-03069-y

    Article  Google Scholar 

  35. Moinuddin, S.Q., Machireddy, V.V., Raghavender, V., Kaniganti, T.B., Sarila, V., Ponnappan, S.M., Shanmugam, R., Cheepu, M.: Analysis on bonding interface during solid state additive manufacturing between 18Cr-8Ni and 42crmo4 high performance alloys. Metals 13(3), 488 (2023). https://doi.org/10.3390/met13030488

    Article  Google Scholar 

  36. Pramod Kumar, G., Balasubramanian, K.R., Phani Prabhakar, K.V., Cheepu, M.: Investigation of microstructure, mechanical, and corrosion properties of Inconel 617 joints welded by laser–MIG hybrid welding. In: Proceedings of the Institution of Mechanical Engineers, Part L: Journal of Materials: Design and Applications (2023). https://doi.org/10.1177/14644207231161992

  37. Kocharla, R.P.B., Kolli, M., Cheepu, M.: Real-time detection of faults in rotating blades using frequency response function analysis. Applied Mechanics 4(1), 356–370 (2023)

    Article  Google Scholar 

  38. Chigilipalli, B.K., Karri, T., Chetti, S.N., Bhiogade, G., Kottala, R.K., Cheepu, M.: A review on recent trends and applications of IoT in additive manufacturing. Appl. Syst. Innov. 6(2), 50 (2023)

    Article  Google Scholar 

  39. Dasari, S.N., Vinjavarapu, S., Cheepu, M.M.: Effect of reinforcement particle size on LM-13-snail shell ash–SiC hybrid metal matrix composite. Waste Residue Comp. 16, 87 (2023)

    Article  Google Scholar 

  40. Dewangan, A.K., Moinuddin, S.Q., Cheepu, M., Sajjan, Ashwani Kumar, S.K.: Thermal energy storage: opportunities, challenges and future scope. Therm. Energy Syst., pp 17–28

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Authors and Affiliations

  1. Department of Mechanical Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, 522302, India

    Jeevan Raju Boddu & P. Venkata Chalapathi

  2. Department of Mechanical Engineering, KKR AND KSR Institute of Technology and Sciences, Guntur, 522017, India

    K. Rama Kotaiah

  3. Department of Mechanical Engineering, Mother Teresa Institute of Science and Technology, Sathupally, 507303, India

    Jakeer Hussain Shaik

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  1. Jeevan Raju Boddu
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Correspondence to Jeevan Raju Boddu.

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Boddu, J.R., Kotaiah, K.R., Chalapathi, P.V. et al. Optimization of design for the high precision end mill spindles to improve stability of effective cutting process. Int J Interact Des Manuf (2023). https://doi.org/10.1007/s12008-023-01526-y

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