Affiliation:
1. Department of Industrial and Manufacturing Engineering, North Dakota State University, Fargo, ND 58105
2. School of Industrial Engineering, Purdue University, West Lafayette, IN 47907
Abstract
The need for predicting material microstructure and hardness in hard turned surfaces becomes very urgent in that hard turning is adopted by industries as a finishing process, and the produced surface integrity, including microstructure and hardness, is well known to be a determining factor for part service performance. This study focuses on the prediction of material softening and is composed of two parts, namely, the construction of material softening model based on thermal history and the prediction of thermal history by finite element modeling of hard turning. In this part of the research, three material softening models based on thermal activation concept are proposed and compared. The most suitable model is selected for the work material, hardened AISI 52100 steel. The model prediction demonstrates excellent agreement with the hardness measurement on the specimens with isothermal or anisothermal treatments. For the isothermal treatments, the average prediction error, compared with the measured hardness, is 10.78kg∕mm2. As for the anisothermal treatments, the average error is 13.79kg∕mm2. The softening model provides a fundamental for the final prediction of material softening in hard turned surfaces.
Subject
Industrial and Manufacturing Engineering,Computer Science Applications,Mechanical Engineering,Control and Systems Engineering
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