Abstract
With the increased usage of Advanced High Strength Steels, galling wear has become a significant challenge for sheet metal stamping industries. Galling, in particular, can have a large economic impact due to the high costs and lost productivity associated with manual monitoring, refinishing/resurfacing damaged tooling and formed parts, and the need to apply expensive treatments or coatings to tool surfaces. This has led to a push for automated galling wear detection systems. However, developing such systems requires an accurate measurement of galling wear severity that can be easily implemented in industrial situations. Parameters used for measuring galling wear are often difficult to collect in large industrial style trials, and can be inaccurate as they are not targeted towards characterising the localised features associated with galling wear damage. In this study, a new galling wear characterisation and measurement methodology is introduced that accurately measures galling wear severity by targeting the localised features on sheet metal parts. This methodology involves calculating Discrete Wavelet Transform detail coefficients of 2D surface profiles. A case study on a series of deep drawn channel parts demonstrates the accuracy of the Discrete Wavelet Transform methodology when compared to visual assessment of galling wear severity. Based on comparison to visual assessment the presented Discrete Wavelet Transform galling wear measurement methodology outperforms other commonly used wear measures. The methodology provides a targeted, repeatable and non-subjective measure of galling wear severity. The specific outcome of this work provides an important tool for research into galling wear monitoring and detection systems in sheet metal forming, and the study of galling wear and its prevention in general.
Original language | English |
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Pages (from-to) | 334-345 |
Number of pages | 12 |
Journal | Wear |
Volume | 390-391 |
DOIs | |
Publication status | Published - 2017 |