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Special Section Papers

A Real-Time Stability Indicator for Micromilling: An Experimental Validation

[+] Author and Article Information
Shashwat Kushwaha

Department of Mechanical Engineering,
KU Leuven,
Celestijnenlaan 300,
Leuven 3001, Belgium
e-mail: shashwat.kushwaha@kuleuven.be

Benjamin Gorissen

Department of Mechanical Engineering,
KU Leuven,
Celestijnenlaan 300,
Leuven 3001, Belgium
e-mail: benjamin.gorissen@kuleuven.be

Jun Qian

Department of Mechanical Engineering,
KU Leuven,
Celestijnenlaan 300,
Leuven 3001, Belgium
e-mail: jun.qian@kuleuven.be

Dominiek Reynaerts

Department of Mechanical Engineering,
KU Leuven,
Celestijnenlaan 300,
Leuven 3001, Belgium
e-mail: dominiek.reynaerts@kuleuven.be

1Corresponding author.

Contributed by the Manufacturing Engineering Division of ASME for publication in the JOURNAL OF MICRO-AND NANO-MANUFACTURING. Manuscript received November 15, 2018; final manuscript received March 18, 2019; published online April 11, 2019. Assoc. Editor: Lawrence Kulinsky.

J. Micro Nano-Manuf 7(1), 010908 (Apr 11, 2019) (6 pages) Paper No: JMNM-18-1055; doi: 10.1115/1.4043275 History: Received November 15, 2018; Revised March 18, 2019

In contrast to the well-established stability prediction tools, a robust real-time stability indicator is proposed for micromilling process, and it opens the possibility of online chatter avoidance based on successful detection. In this paper, a robust and easy-to-compute stability indicator is presented. This approach exploits the virtue of a stable milling process—the displacement of the vibrating tool repeats with a period of tooth passing. It has been observed that the standard deviation of the tool displacement sampled at once per tooth passing frequency is indicative of chatter, where a low standard deviation coincides with stable cutting. An increase in standard deviation is the direct consequence of an increase in asynchronous motion of the tool, coinciding with chatter. As it is also well known, this asynchronous vibration of the tool results in distinct marks on the workpiece surface. This paper presents the experimental validation of this real-time stability indicator. The ease of implementation makes the presented stability indicator a strong candidate for applications in chatter avoidance based on detection. The results are also verified against the standard stability prediction method.

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References

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Figures

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Fig. 1

Schematic of dynamic model of cutting simulation

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Fig. 2

Milling geometry: cutting forces and tool displacement

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Fig. 3

(a) Machining experiment setup, (b) slot geometry, and (c) SEM images of a tool after machining 200 mm (four slots), d = 1.5 mm, z = 1

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Fig. 4

(a) Time series data with an overlay of stroboscopically sampled data and an image of slot at the onset of chatter; (b) spectrum, left: stable, right: unstable; (c) synchronous and asynchronous error motion plot, left set: stable, right set: unstable; (d) error motion plotted against time of cut; (e) Poincaré sections at left set: stable, right set: unstable; and (f) stability indicator plotted against time of cut

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Fig. 5

Stability indicator

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Fig. 6

Poincaré section for d = 1 mm, z = 4, and S = 37,000 RPM: (a) ap= 0.45 mm, stable and (b) ap= 0.91 mm, unstable

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Fig. 7

Measured and indirectly estimated FRF

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Fig. 8

Stability lobe diagram, d = 1 mm

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