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Monitoring of surface roughness evolution during abrasive flow machining by acoustic emission

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Abstract

Abrasive flow machining (AFM) is very effective and widely adopted superfinishing process of internal channel surfaces in industry. There have been high demands for process monitoring of surface roughness evolution during AFM, as the evolution of surface roughness is sensitive to AFM medium variables, such as abrasive grain size and concentration, as well as process duration. Acoustic emission (AE) is known to be a promising tool to detect microscale deformation mechanisms arising from abrasion. This work has shown that there is a close correlation, during AFM with different media, between the evolution of surface roughness and material removal with the AE root mean square (RMS) and AE fast Fourier transform (FFT) signals. Moreover, AE signals are correlated to wear mechanisms, such as plowing and cutting mechanisms.

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Abbreviations

D 1 :

Diameter of the internal channel of the workpiece (mm)

D 2 :

Inner diameter of the cylinder of AFM machine (mm)

P :

Extrusion pressure of the AFM machine (bar)

N :

Number of cycles of AFM operation ()

\({v}_{1}\) :

Velocity of medium flow in the internal channel of the workpiece (mm/sec)

\({v}_{2}\) :

Velocity of medium flow in the cylinder of the AFM machine (mm/sec)

A 1 :

Cross-sectional area of the internal channel in the workpiece (mm)

A 2 :

Cross-sectional area of the cylinder in the AFM machine (mm)

\({Q}_{\mathrm{cycle}}\) :

Volume flow rate (mm3/sec)

\({V}_{\mathrm{cycle}}\) :

AFM medium volume for one cycle of AFM process (mm3)

\({t}_{\mathrm{cycle}}\) :

One cycle time of AFM process (sec)

Sa :

Arithmetical mean height (µm)

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Acknowledgements

The authors are grateful to “I@L Carnot MELTED” for funding this research. Special thanks to Extrude Hone for providing an AFM machine, media, and sensors.

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Authors and Affiliations

  1. Ecole Centrale de Lyon - ENISE, LTDS, UMR CNRS 5513, 58 Rue Jean Parot, 42023, Saint-Étienne, France

    Sangil Han, Ferdinando Salvatore, Christophe Claudin & Joël Rech

  2. Extrude Hone, Bgm.-Merk-Str. 1, 87752, Holzgünz, Germany

    Fabio Wosniak & Patrick Matt

Authors
  1. Sangil Han
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  2. Ferdinando Salvatore
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  3. Christophe Claudin
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  4. Joël Rech
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  5. Fabio Wosniak
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Contributions

Sangil Han: investigation, analysis of research results, writing—original draft, editing; Ferdinando Salvatore: funding supervision, review; Christophe Claudin: experimental set-up; Joël Rech: funding, resource, supervision, review—editing; Fabio Wosniak: resource, methodology, review; Patrick Matt: resource.

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Correspondence to Sangil Han.

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Appendix

Appendix

1.1 A.1. Effective pressure signals

As discussed in Sect. 2.2, effective pressure signals were measured with 3 replications at specific cycles—1, 10, 25, 50, 75, 100, and 150 cycles. Effective pressure signals at two pressure sensors (X = 0 and 14 mm in Fig. 2) are shown in Fig. 

Fig. 13
figure 13

Effective pressure signals at 100 cycles in AFM with 50%-54: effective pressure a at X = 0 mm and b at X = 14 mm

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13. Up- and down-strokes are indicated in those effective pressure signals. Evolution of effective signals at X = 0 and 14 mm in AFM with all AFM media for 150 cycles is shown in Figs. 13 and

Fig. 14
figure 14

Evolution of effective pressures at X = 0 mm in AFM with all AFM media for 150 cycles: a up-stroke and b down-stroke

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14. Variation of the effective pressures in AFM for 150 cycles is not significant as shown in Figs. 13 and 14.

Fig. 15
figure 15

Evolution of effective pressures at X = 14 mm in AFM with all AFM media for 150 cycles: a up-stroke and b down-stroke

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Han, S., Salvatore, F., Claudin, C. et al. Monitoring of surface roughness evolution during abrasive flow machining by acoustic emission. Int J Adv Manuf Technol 131, 595–609 (2024). https://doi.org/10.1007/s00170-023-11229-z

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