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Experimental verification of design methodology for chatter suppression in tool swing–assisted parallel turning

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Abstract

Parallel turning has the potential in enhancing the machining productivity and consequently reducing total production costs. However, due to the complex interaction of tools and workpieces, the stability of the process against chatter vibration is often decreased; hence, a successful chatter avoidance/suppression must be achieved. Recently, our research group suppressed the chatter in the shred-surface parallel turning by oscillating two tools in the circumferential direction of a flexible workpiece while keeping the equal pitch. However, there are insufficient discussion and experimental verification surrounding the optimal design for the tool swing motion (TSM). This paper presents a design methodology for the tool swing parallel turning based on the analogy with the spindle speed variation (SSV) techniques. A series of experiments were conducted while varying TSM design parameters to support the proposed design method. In-depth discussions regarding the experimental results were also carried out. The results of this study provide adequate information for properly tuning the TSM process for effective chatter suppression in practical applications.

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Abbreviations

a t :

Acceleration of stage (m/s2)

GLPF(s):

Low-pass filter (-)

fc, ωc :

Chatter frequency (Hz) (ωc = 2πfc (rad/s))

F cut :

Cutting force (N)

Ffric, Tfric :

Friction force and torque (N, Nm)

F grav :

Gravity force (N)

fsw, ωsw :

Tool swing frequency (Hz), (ωsw = 2πfsw (rad/s))

\( {I}_a^{\mathrm{ref}} \) :

Motor current reference (A)

J r :

Total inertia of motor, coupling, and ball screw (kgm2)

k :

Chatter lobe number (-)

K t :

Torque coefficient (Nm/A)

M t :

Movable mass (kg)

N :

Number of teeth/cutters (-)

R :

Transform coefficient for rotational to translational motion (mm/rad)

RVA :

Relative amplitude of spindle speed variation against the mean (nominal) spindle speed (-)

RVA opt :

Optimal value of RVA (-)

RVF :

Relative frequency of spindle speed variation against the mean (nominal) spindle speed (-)

RVF lim :

Lower limit value of RVF (-)

S :

Spindle speed (min-1)

S rel :

Relative spindle speed in TSM process (min-1)

t :

Process time (s)

α r :

Angular acceleration (rad/s2)

ε :

Chatter phase shift (rad)

θ :

Tool swing angle in TSM process (rad)

θ 0 :

Offset angle in TSM process (rad)

θ sw :

Amplitude of swing angle in TSM process (rad)

ρ :

Amplitude ratio of the expected and the real delay term representing the efficiency of TSM process (-)

τ :

Real delay in TSM process (s)

\( \overset{\sim }{\tau } \) :

Expected delay in TSM process (s)

\( \left(\hat{\mkern6mu}\right) \) :

Estimated value

()n :

Nominal value

References

  1. Budak E, Ozturk E (2011) Dynamics and stability of parallel turning operations. CIRP Ann Manuf Technol 60(1):383–386. https://doi.org/10.1016/j.cirp.2011.03.028

    Article  Google Scholar 

  2. Azvar M, Budak E (2017) Multi-dimensional chatter stability for enhanced productivity in different parallel turning strategies. Int J Mach Tools Manuf 123:116–128. https://doi.org/10.1016/j.ijmachtools.2017.08.005

    Article  Google Scholar 

  3. Ozturk E, Comak A, Budak E (2016) Tuning of tool dynamics for increased stability of parallel (simultaneous) turning processes. J Sound Vib 360(6):17–30. https://doi.org/10.1016/j.jsv.2015.09.009

    Article  Google Scholar 

  4. Reith MJ, Bachrathy D, Stepan G (2016) Optimal Detuning of a parallel turning system—theory and experiments. J Dyn Syst Meas Control 139(1):014503. https://doi.org/10.1115/1.4034497

    Article  Google Scholar 

  5. Brecher C, Trofimov Y, Bäumler S (2011) Holistic modelling of process machine interactions in parallel milling. CIRP Ann Manuf Technol 60(1):387–390. https://doi.org/10.1016/j.cirp.2011.03.025

    Article  Google Scholar 

  6. Sakata S, Kadota T, Yamada Y, Nakanishi K, Yoshioka H, Suzuki N, Kakinuma Y (2018) Chatter avoidance in parallel turning with unequal pitch angle using observer-based cutting force estimation. J Manuf Sci Eng 140(4):044501. https://doi.org/10.1115/1.4039111

    Article  Google Scholar 

  7. Yamato S, Yamada Y, Nakanishi K, Suzuki N, Yoshioka H, Kakinuma Y (2018) Integrated in-process chatter monitoring and automatic suppression with adaptive pitch control in parallel turning. Adv Manuf 6(3):291–300. https://doi.org/10.1007/s40436-018-0222-0

    Article  Google Scholar 

  8. Yamato S, Okuma T, Nakanishi K, Tachibana J, Suzuki N, Kakinuma Y (2019) Chatter suppression in parallel turning assisted with tool swing motion provided by feed system. Int J Autom Technol 13(1):80–91. https://doi.org/10.20965/ijat.2019.p0080

    Article  Google Scholar 

  9. Al-Regib E, Ni J, Lee SH (2003) Programming spindle speed variation for machine tool chatter suppression. Int J Mach Tools Manuf 43(12):1229–1240. https://doi.org/10.1016/S0890-6955(03)00126-3

    Article  Google Scholar 

  10. Otto A, Radons G (2013) Application of spindle speed variation for chatter suppression in turning. CIRP J Manuf Sci Technol 6(2):102–109. https://doi.org/10.1016/j.cirpj.2013.02.002

    Article  Google Scholar 

  11. Urbikain G, Olvera D, de Lacalle LNL, Elías-Zúñiga A (2016) Spindle speed variation technique in turning operations: modeling and real implementation. J Sound Vib 383(24):384–396. https://doi.org/10.1016/j.jsv.2016.07.033

    Article  Google Scholar 

  12. Hecker RL, Flores GM, Xie Q, Haran R (2008) Servocontrol of machine-tools: a review. Lat Am Appl Res 38:85–94

    Google Scholar 

  13. Altintas Y, Verl A, Brecher C, Uriarte L, Pritschow G (2011) Machine tool feed drives. CIRP Ann Manuf Technol 60(2):779–796. https://doi.org/10.1016/j.cirp.2011.05.010

    Article  Google Scholar 

  14. Yamada Y, Kakinuma Y (2016) Sensorless cutting force estimation for full-closed controlled ball-screw-driven stage. Int J Adv Manuf Technol 87:3337–3348. https://doi.org/10.1007/s00170-016-8710-5

    Article  Google Scholar 

  15. Yamada Y, Kadota T, Sakata S, Tachibana J, Nakanishi K, Sawada M, Kakinuma Y (2017) Integrated chatter monitoring based on sensorless cutting force/torque estimation in parallel turning. Int J Autom Technol 11(2):215–225. https://doi.org/10.20965/ijat.2017.p0215

    Article  Google Scholar 

  16. Munoa J, Beudaert X, Dombovari Z, Altintas Y, Budak E, Brecher C, Stepan G (2016) Chatter suppression techniques in metal cutting. CIRP Ann Manuf Technol 65(2):785–808. https://doi.org/10.1016/j.cirp.2016.06.004

    Article  Google Scholar 

  17. Insperger T, Stepan G (2004) Stability analysis of turning with periodic spindle speed modulation via semidiscretization. J Vib Control 10(12):1835–1855. https://doi.org/10.1177/1077546304044891

    Article  MATH  Google Scholar 

  18. Zatarain M, Bediaga I, Muñoa J, Lizarralde R (2008) Stability of milling processes with continuous spindle speed variation: Analysis in the frequency and time domains, and experimental correlation. CIRP Ann Manuf Technol 57(1):379–384. https://doi.org/10.1016/j.cirp.2008.03.067

    Article  Google Scholar 

  19. Jemielniak K, Widota A (1984) Suppression of self-excited vibration by the spindle speed variation method. Int J Mach Tool Des Res 24(3):207–214

    Article  Google Scholar 

  20. Jayaram S, Kapoor SG, DeVor RE (2000) Analytical stability analysis of variable spindle speed machining. J Manuf Sci Eng 122(3):391–397. https://doi.org/10.1016/0020-7357(84)90005-2

    Article  Google Scholar 

  21. Tunç LT, Budak E (2012) Effect of cutting conditions and tool geometry on process damping in machining. Int J Mach Tools Manuf 57:10–19. https://doi.org/10.1016/j.ijmachtools.2012.01.009

    Article  Google Scholar 

  22. Ahmadi K, Ismail F (2011) Analytical stability lobes including nonlinear process damping effect on machining chatter. Int J Mach Tools Manuf 51(4):296–308. https://doi.org/10.1016/j.ijmachtools.2010.12.008

    Article  Google Scholar 

  23. Liu CR, Liu TM (1985) Automated chatter suppression by tool geometry control. J Eng Ind 107(2):95–98. https://doi.org/10.1115/1.3185989

    Article  Google Scholar 

  24. Sellmeier V, Denkena B (2012) High speed process damping in milling. CIRP J Manuf Sci Technol 5(1):8–19. https://doi.org/10.1016/j.cirpj.2011.12.001

    Article  Google Scholar 

  25. Tarng YS, Young HT, Lee BY (1994) An analytical model of chatter vibration in metal cutting. Int J Mach Tools Manuf 34(2):183–197. https://doi.org/10.1016/0890-6955(94)90100-7

    Article  Google Scholar 

  26. Altintas Y, Weck M (2004) Chatter stability of metal cutting and grinding. CIRP Ann Manuf Technol 53(2):619–642. https://doi.org/10.1016/S0007-8506(07)60032-8

    Article  Google Scholar 

  27. Radulescu R, Kapoor SG, DeVor RE (1997) An investigation of variable spindle speed face milling for tool-work structures with complex dynamics, part 2: Physical explanation. J Manuf Sci Eng Trans ASME 119(3):273–280. https://doi.org/10.1115/1.2831104

    Article  Google Scholar 

  28. Albertelli P, Mussi V, Monno M (2014) The analysis of tool life and wear mechanisms in spindle speed variation machining. Int J Adv Manuf Technol 72:1051–1061. https://doi.org/10.1007/s00170-014-5736-4

    Article  Google Scholar 

  29. Suzuki N, Takahashi W, Igeta H, Nakanomiya T (2020) Flank face texture design to suppress chatter vibration in cutting. CIRP Ann 69(1):93–96. https://doi.org/10.1016/j.cirp.2020.04.037

    Article  Google Scholar 

  30. Kayhan M, Budak E (2009) An experimental investigation of chatter effects on tool life. Proc Inst Mech Eng B J Eng Manuf 223(11):1455–1463. https://doi.org/10.1243/09544054JEM1506

    Article  Google Scholar 

  31. Merino R, Bediaga I, Iglesias A, Munoa J (2019) Hybrid edge-cloud-based smart system for chatter suppression in train wheel repair. Appl Sci 9(20):4283. https://doi.org/10.3390/app9204283

    Article  Google Scholar 

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Acknowledgments

The authors thank Mr. Okuma and OMRON Corporation for their support and assistance for this research.

Funding

A part of this study was supported by SIP Innovative Design and Production Technology Project commissioned by the New Energy and Industrial Technology Development Organization (NEDO) and JSPS Grant-in-Aid for JSPS Fellows Grant Numbers JP19J13204.

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Correspondence to Shuntaro Yamato.

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Appendix

Appendix

In the TSM process, the process time delay is a time function. In the tool swing parallel turning, as two tools oscillate according to Eq. (5) while keeping the equal pitch, the following equation should hold:

$$ {\int}_{t-\tau (t)}^t\frac{2\pi {S}_n}{60} dt=\pi +{\theta}_{sw}\sin \left({\omega}_{sw}t\right)-{\theta}_{sw}\sin \left({\omega}_{sw}\left(t-\tau (t)\right)\right) $$
(10)

The delay satisfying Eq. (10) can be calculated by numerical calculations such as the Newton-Raphson method, once the cutting conditions and time-varying profile of TSM are determined.

On the other hand, the expected time-varying delay in the TSM process, straightforwardly derived from Eq. (6), is as follows:

$$ \kern2.75em {\displaystyle \begin{array}{c}\overset{\sim }{\tau }=\frac{60}{N{S}_{rel}}=\frac{60}{N{S}_n\left(1-\frac{60{\theta}_{sw}{\omega}_{sw}}{2\uppi {S}_n}\cdotp \cos \left({\omega}_{sw}t\right)\right)}\kern0.75em \\ {}=\frac{60}{N{S}_n\left(1- RVA\cdotp \cos \left({\omega}_{sw}t\right)\right)}\end{array}} $$
(11)

As a result, the amplitude ratio representing efficiency of TSM process can be defined as follows:

$$ \rho =\frac{\left\{\max \left(\tau (t)\right)-\min \left(\tau (t)\right)\right\}/2}{\left\{\max \left(\overset{\sim }{\tau }(t)\right)-\min \left(\overset{\sim }{\tau }(t)\right)\right\}/2}=\frac{A_{\tau }}{A_{\overset{\sim }{\tau }}} $$
(12)

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Yamato, S., Nakanishi, K., Suzuki, N. et al. Experimental verification of design methodology for chatter suppression in tool swing–assisted parallel turning. Int J Adv Manuf Technol 110, 1759–1771 (2020). https://doi.org/10.1007/s00170-020-05951-1

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