Efficient determination of stability lobe diagrams by in-process varying of spindle speed and cutting depth

Abstract

The experimental determination of stability lobe diagrams (SLDs) in milling can be realized by either continuously varying the spindle speed or by varying the depth of cut. In this paper, a method for combining both these methods along with an online chatter detection algorithm is proposed for efficient determination of SLDs. To accomplish this, communication between the machine control and chatter detection algorithm is established, and the machine axes are controlled to change the spindle speed or depth of cut. The efficiency of the proposed method is analyzed in this paper.

Keywords

Chatter detection / Poincaré / Cutting depth variation / Spindle speed

References

[1] Tlusty J, Ismail F. Basic non-linearity in machining chatter. Ann CIRP, 1981, 30: 299-304.

[2] Altintas Y, Budak E. Analytical prediction of stability lobes in milling. Ann CIRP, 1995, 44: 357-362.

[3] Altintas Y, Budak E. Analytical prediction of chatter stability in milling—part I: general formulation. J Dyn Syst Meas Control, 1998, 120(1): 22-30.

[4] Altintas Y, Budak E. Analytical prediction of chatter stability in milling—part II: application of the general formulation to common milling systems. J Dyn Syst Meas Control, 1998, 120(1): 31-36.

[5] Quintana G, Ciurana J, Teixidor D. A new experimental methodology for identification of stability lobes diagram in milling operations. Mach Tools Manuf, 2008, 48: 1637-1645.

[6] Grossi N, Scippa A, Sallese L, et al. Spindle speed ramp-up test: a novel experimental approach for chatter stability detection. Mach Tools Manuf, 2015, 89: 221-230.

[7] Davies MA, Dutterer B, Pratt JR, et al. On the dynamics of high-speed milling with long, slender endmills. Ann CIRP, 1998, 47: 55-60.

[8] Surmann T (2005) Geometric-physical simulation of the process dynamics for five-axis milling of free-form surface. Dissertation, Dortmund University

[9] Honeycutt A, Schmitz T. A new metric for automated stability identification in time domain milling simulation. J Manuf Sci Eng, 2016, 138(7): 074501.

[10] Schmitz T, Medicus K, Dutterer B. Exploring once-per-revolution audio signal variance as a chatter indicator. Mach Sci Technol, 2002, 6(2): 215-233.

[11] Brecher C, Epple A, Fey M. Efficient determination of optimal process parameter. wtWerkstatttechnik online, 2014, 104: 260-265.

[12] Brecher C, Kiesewetter C, Epple A, et al. Automated creation of stability lobes diagrams for milling. ZWF, 2015, 110(4): 191-195.

[13] Brecher C, Chavan P, Epple A. Efficient determination of stability boundaries. wtWerkstattstechnik online, 2017, 107(5): 313-317.

[14] Brecher C, Daniels M, Wellmann F et al (2015) Realisation of efficient cutting processes. Result report of the BMBF—joint project ReffiZ. Shaker-Verlag, Aachen

Funding

Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659(BR 2905/73-1)