Title :
Performance comparison of artificial neural network and expert system in prediction of flow stress
Author_Institution :
Sch. of Mech. Eng., Dalian Univ. of Technol., Dalian, China
Abstract :
Modeling of various manufacturing processes, including force and power requirements, depends on accurate estimation of a material´s flow stress. The paper presents a mutual comparison between rule-based expert system and artificial neural network in predicting flow stress of a commonly used type of steel. The prediction processes take microstructure, applied temperature, strain, and strain rate as process parameters. The prediction results of both the systems show a good deal of match with the actual values.
Keywords :
crystal microstructure; expert systems; manufacturing processes; materials science computing; neural nets; plastic flow; steel; artificial neural network; flow stress prediction; force requirements; manufacturing processes; material flow stress estimation; microstructure; power requirements; process parameters; rule-based expert system; steel; strain rate; temperature; Artificial neural networks; Expert systems; Materials; Microstructure; Steel; Strain; Stress; AISI 4340; fuzzy reasoning; properties estimation; rule-based system;
Conference_Titel :
Industrial Electronics and Applications (ICIEA), 2013 8th IEEE Conference on
Conference_Location :
Melbourne, VIC
Print_ISBN :
978-1-4673-6320-4
DOI :
10.1109/ICIEA.2013.6566431