Method for the Estimation of Wear Resistance Curves in Sheet Metal Forming with Uncoated Tools

Abstract:

The wear resistance diagram (WRD) is a useful tool for quantitatively estimating the life span of a tribological system in sheet metal forming at different load levels. However, the WRD derived from the authors’ previous research consists merely of scattered points, which make it difficult to reliably estimate the life span and its uncertainties at all load levels. Therefore, a wear resistance curve (WRC) that encompasses the life spans of all load levels is required for a broader scope of application of wear resistance estimation. In this paper, different models for the estimation of the S-N curve describing the fatigue behavior are tested to investigate their applicability in the estimation of wear resistance curves (WRC) in sheet metal forming. WRDs of different tribological systems are investigated and the results of curve fitting are evaluated. Besides the median of the estimated life spans, the WRCs of different confidence levels are also derived quantile calculation to estimate the load dependent uncertainties of tool life spans. Moreover, due to the time-consuming experiments to determine tool life, it is necessary to discuss possibilities for achieving a satisfactory estimation with the smallest possible number of tests. Therefore, the minimal number of tests and the suitable load levels for a satisfactory estimation will be discussed. After the study, several findings have been obtained:Compared to other models, Hwang and Han’s model for estimating fatigue life of composite material shows good applicability and the highest accuracy in estimating the WRC of uncoated tools.In terms of damage development, the fatigue damage of the composite material and the damage caused by wear on uncoated tools have similarities, which explains the applicability of Hwang and Han’s model for the estimation of WRC.Both higher and lower life wear data are the prerequisite for satisfactory wear estimation.

• Periodical: Key Engineering Materials (Volume 926)
• Pages: 1151-1167
• DOI: https://doi.org/10.4028/p-26i1sy
• Online since: July 2022
• Authors: Yu Tian Wu*, Rui Zhe Li, Peter Groche
• Keywords: Forming Technology, Life Span Prediction, S-N Curve, Tribology, Wear Resistance

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