Distribution & Access For Publication Downloads News About Us Contact Us
Paper Titles
A Damage Mechanics Based Cohesive Zone Model with Damage Gradient Extension for Creep-Fatigue-Interaction
p.253
Finite Element Calculation of Anisotropy of Hole Expansion in a Thin Steel Sheet with Six Degrees Polynomial Yield Function
p.260
A Springback Prediction of 1.5 GPa Grade Steel in Roll Forming Process for Automotive Sill-Side Inner Component
p.267
Data-Driven Compensation for Bulk Formed Parts Based on Material Point Tracking
p.277
Investigation of Stamping Tool Wear Initiation at Microscopic Level Using Acoustic Emission Sensors
p.285
Ultra-Thin Sheet Forming Analyses Considering Size Effects
p.295
High Temperature Deformation Behavior and Processing Maps of AZ31 Alloy Deformed in Tension versus Compression
p.305
Numerical and Experimental Study on ECAP-Processing Parameters for Efficient Grain Refinement of AA5083 Sheet Metal
p.315
Evaluation of Effect of Sample Size and Layer Direction on Mechanical Property of Specimen Manufactured by FDM-Type 3D Printer
p.324

Investigation of Stamping Tool Wear Initiation at Microscopic Level Using Acoustic Emission Sensors

Article Preview

Abstract:

Stamping tools are prone to an adhesive wear mode called galling. Adhesive wear on stamping tools can degrade the product quality and can affect the mass production. Even a small improvement in the maintenance process is beneficial for the stamping industry. Therefore, this study will focus on understanding and detecting the initiation of tool wear at the microscopic level in sheet metal stamping using acoustic emission sensors. Stamping tests were performed using a semi-industrial stamping process, which can perform clamping, piercing, stamping and trimming in a single cycle. The stamping test was performed using a high strength low alloy sheet steel and D2 tool steel for dry and lubricated conditions. The acoustic emission signal was recorded for each stamped part until severe wear on the dies was observed. These acoustic emission signals were later analyzed using time and frequency domain features. The time domain features such as peak, RMS, kurtosis and skewness could identify significant changes in the acoustic emission signal only when the severe wear was observed on the stamped parts for both dry and lubricated conditions. However, this study has identified that a frequency feature – known as mean-frequency estimate – could identify early stages of wear initiation at the microscopic level. Evidence of this early stage of wear on the part surfaces was not clearly visible to the naked eye, and could only be clearly observed via surface measurement instruments such as an optical profilometer. The sidewalls of the stamped parts corresponding to the initial change in AE mean-frequency trend were qualitatively correlated with 3D profilometer scans of the stamped parts, to show that AE mean-frequency can indicate the initial minor scratches on the sidewalls of the stamped parts due to the galling wear on the die radii surfaces. The results from this study can be used to develop a methodology to determine the very early stages of stamping tool wear, providing a strong basis for condition monitoring in the stamping industry.

You might also be interested in these eBooks
Advances in Engineering Plasticity and its Application IX View Preview

Info:

Periodical:

Key Engineering Materials (Volume 794)

Pages:

285-294

DOI:

https://doi.org/10.4028/www.scientific.net/KEM.794.285

Citation:

Cite this paper

Online since:

February 2019

Authors:

Vignesh V. Shanbhag*, Bernard F. Rolfe, Narayanan Arunachalam, Michael P. Pereira

Keywords:

Acoustic Emission, Galling, Mean-Frequency, Peak, Stamping

Export:

RIS, BibTeX

Price:

Permissions:

Request Permissions

* - Corresponding Author

References

[1] Jin J, Shi J. Diagnostic feature extraction from stamping tonnage signals based on design of experiments. Journal of manufacturing science and engineering. 2000;122(2):360-369.

DOI: 10.1115/1.538926

Google Scholar

[2] Cora ON, Koç M, editors. Experimental investigations on wear resistance characteristics of alternative die materials for stamping of Advanced High Strength Steels (AHSS). ASME 2008 International Manufacturing Science and Engineering Conference collocated with the 3rd JSME/ASME International Conference on Materials and Processing; 2008: American Society of Mechanical Engineers. 185-191.

DOI: 10.1115/msec_icmp2008-72027

Google Scholar

[3] de Rooij MB, Schipper DJ. Analysis of material transfer from a soft workpiece to a hard tool: Part I—Lump growth model. Journal of tribology. 2001;123(3):469-473.

DOI: 10.1115/1.1308009

Google Scholar

[4] Gåård A, Krakhmalev P, Bergström J, Hallbäck N. Galling resistance and wear mechanisms–cold work tool materials sliding against carbon steel sheets. Tribology letters. 2007;26(1):67-72.

DOI: 10.1007/s11249-006-9186-5

Google Scholar

[5] Skåre T, Krantz F. Wear and frictional behaviour of high strength steel in stamping monitored by acoustic emission technique. Wear. 2003;255(7-12):1471-1479.

DOI: 10.1016/s0043-1648(03)00197-2

Google Scholar

[6] Shanbhag VV, Pereira PM, Rolfe FB, Arunachalam N, editors. Time series analysis of tool wear in sheet metal stamping using acoustic emission. Journal of Physics: Conference Series; 2017 Sep (Vol. 896, No. 1, p.012030). IOP Publishing.

DOI: 10.1088/1742-6596/896/1/012030

Google Scholar

[7] Shanbhag VV, Rolfe BF, Arunachalam N, Pereira MP. Investigating wear behaviour in sheet metal stamping using acoustic emissions. Wear. (2018).

DOI: 10.1016/j.wear.2018.07.003

Google Scholar

[8] Hase A, Mishina H, Wada M. Correlation between features of acoustic emission signals and mechanical wear mechanisms. Wear. 2012;292:144-150.

DOI: 10.1016/j.wear.2012.05.019

Google Scholar

[9] Sindi CT, Najafabadi MA, Salehi M. Tribological behavior of sheet metal forming process using acoustic emission characteristics. Tribology Letters. 2013;52(1):67-79.

DOI: 10.1007/s11249-013-0193-z

Google Scholar

[10] Nectoux P, Gouriveau R, Medjaher K, Ramasso E, Chebel-Morello B, Zerhouni N, et al., editors. PRONOSTIA: An experimental platform for bearings accelerated degradation tests. IEEE International Conference on Prognostics and Health Management, PHM'12; 2012: IEEE Catalog Number: CPF12PHM-CDR.

DOI: 10.51257/a-v1-mt9570

Google Scholar

[11] Huang R, Xi L, Li X, Liu CR, Qiu H, Lee J. Residual life predictions for ball bearings based on self-organizing map and back propagation neural network methods. Mechanical systems and signal processing. 2007;21(1):193-207.

DOI: 10.1016/j.ymssp.2005.11.008

Google Scholar

[12] Information on https://www.ita- polska.com.pl/upload/documents/IF-MeasureSuite_5.1_ProductInfo_EN1.pdf (IF-MeasurementSuite 5.1. Retrieved on Jan 21, 2017).

Google Scholar

[13] Pereira MP, Weiss M, Rolfe BF, Hilditch TB. The effect of the die radius profile accuracy on wear in sheet metal stamping. International Journal of Machine Tools and Manufacture. 2013;66:44-53.

DOI: 10.1016/j.ijmachtools.2012.11.001

Google Scholar

[14] Lei Y, He Z, Zi Y, Chen X. New clustering algorithm-based fault diagnosis using compensation distance evaluation technique. Mechanical Systems and Signal Processing. 2008;22(2):419-435.

DOI: 10.1016/j.ymssp.2007.07.013

Google Scholar

[15] Peng Z, Peter WT, Chu F. A comparison study of improved Hilbert–Huang transform and wavelet transform: application to fault diagnosis for rolling bearing. Mechanical systems and signal processing. 2005;19(5):974-988.

DOI: 10.1016/j.ymssp.2004.01.006

Google Scholar

[16] Bassiuny A, Li X, Du R. Fault diagnosis of stamping process based on empirical mode decomposition and learning vector quantization. International Journal of Machine Tools and Manufacture. 2007;47(15):2298-2306.

DOI: 10.1016/j.ijmachtools.2007.06.006

Google Scholar

Scientific.Net is a registered brand of Trans Tech Publications Ltd
© 2024 by Trans Tech Publications Ltd. All Rights Reserved