Bushing Wear Prediction of High-Speed Press Conditions.

Saved in:
Bibliographic Details
Title: Bushing Wear Prediction of High-Speed Press Conditions.
Authors: Yuldoshev, Alibek1 (AUTHOR), Kim, Inseo1 (AUTHOR), Park, Joonhee1 (AUTHOR), Chung, Junhee1 (AUTHOR), Im, Taeyoung1 (AUTHOR), Kim, Naksoo1 (AUTHOR) nskim@sogang.ac.kr
Source: Materials (1996-1944). Jun2026, Vol. 19 Issue 12, p2614. 28p.
Subjects: Finite element method, Prediction models, Power presses, Mechanical failures, Model validation
Abstract: High-speed press systems operate under severe dynamic loading conditions, where bushing components are subject to accelerated wear that directly affects system reliability and maintenance cost. Despite extensive studies on bearing wear in automotive and aerospace applications, wear behavior under high-speed press conditions remains insufficiently explored. This study proposes a wear prediction model that integrates experimental measurements with finite element analysis (FEA). A key hypothesis is that bushing wear under high-speed press conditions can be accurately described by an extended Archard wear model incorporating contact pressure distribution and shaft misalignment effects. A controlled experimental setup was developed to replicate real operating conditions. Wear profiles were measured using high-resolution profilometry, while corresponding contact pressure distributions were obtained via 3D FEA simulations. Model parameters were calibrated using a subset of experimental data and validated against independent test cases. The proposed model demonstrates strong predictive capability, achieving an RMSE of 0.98 μ m and an MAE of 0.57 μ m across the 30-min calibration cases under the average (AVG) load-cell calibration. The extended formulation captures the asymmetric wear patterns induced by misalignment and resolves the high-pressure peak underestimation observed in the plain Archard baseline. [ABSTRACT FROM AUTHOR]
Copyright of Materials (1996-1944) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
Full text is not displayed to guests.
Description
Abstract:High-speed press systems operate under severe dynamic loading conditions, where bushing components are subject to accelerated wear that directly affects system reliability and maintenance cost. Despite extensive studies on bearing wear in automotive and aerospace applications, wear behavior under high-speed press conditions remains insufficiently explored. This study proposes a wear prediction model that integrates experimental measurements with finite element analysis (FEA). A key hypothesis is that bushing wear under high-speed press conditions can be accurately described by an extended Archard wear model incorporating contact pressure distribution and shaft misalignment effects. A controlled experimental setup was developed to replicate real operating conditions. Wear profiles were measured using high-resolution profilometry, while corresponding contact pressure distributions were obtained via 3D FEA simulations. Model parameters were calibrated using a subset of experimental data and validated against independent test cases. The proposed model demonstrates strong predictive capability, achieving an RMSE of 0.98 μ m and an MAE of 0.57 μ m across the 30-min calibration cases under the average (AVG) load-cell calibration. The extended formulation captures the asymmetric wear patterns induced by misalignment and resolves the high-pressure peak underestimation observed in the plain Archard baseline. [ABSTRACT FROM AUTHOR]
ISSN:19961944
DOI:10.3390/ma19122614