Abstract
The fatigue life prediction method using numerical analysis is the latest evaluation technology to predict the fatigue life using the stress data obtained from the structural analysis in order to reduce the evaluation time and cost. A rolling mill is a machine that produces a coil by rolling the material by a roller and the spindle of the rolling mill device serves to transmit the power to the rollers by periodically rotating by the motor. These spindles consist of universal joints, shafts and bearings to deliver power to the rollers. The spindle of the rolling mill is always exposed to the environment subjected to the fatigue load due to the rotation moment by the periodic rotation and there is possibility of the breakage accident due to this. It is very important to prevent breakage by predicting the fatigue life of the spindle in a dynamic operating environment. Therefore, in this study, dynamic stress analysis is performed considering the actual rotating environment conditions using ADINA. Based on the results of stress analysis, we want to predict fatigue life considering dynamic operating environment using WINLIFE that is used for the evaluation of the fatigue life of single shafts, multi-shafts, and gear bearings. Fatigue life analysis of the spindle of the rolling mill using linear cumulative damage theory using S-N curve and equivalent stress was performed in order to evaluate the fatigue life. Stress-life fatigue theory is a method of calculating the lifetime by the minimum input showing the fatigue characteristics of the material.
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Eui Soo Kim is a Professor of Safety Engineering, Korea National University of Transportation, Chungju-si, Chungbuk, Korea. He received his Ph.D. in Mechanical Engineering from Pusan National University. His research interests include Mechanical safety engineering such as computational numerical analysis, forensic engineering, failure analysis, optimal design.
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Kim, E.S. Fatigue life evaluation of spindle of rolling mill using ADINA structure and WINLIFE. J Mech Sci Technol 34, 3991–3996 (2020). https://doi.org/10.1007/s12206-020-2209-6
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DOI: https://doi.org/10.1007/s12206-020-2209-6