Title
Establishment of Relationships between Material Design and Product Design Domains by Hybrid FEM-ANN Technique
Abstract
In this paper, research on AI based modeling technique to optimize development of new alloys with necessitated improvements in properties and chemical mixture over existing alloys as per functional requirements of product is done. The current research work novels AI in lieu of predictions to establish association between material and product customary. Advanced computational simulation techniques like CFD, FEA interrogations are made viable to authenticate product dynamics in context to experimental investigations. Accordingly, the current research is focused towards binding relationships between material design and product design domains. The input to feed forward back propagation prediction network model constitutes of material design features. Parameters relevant to product design strategies are furnished as target outputs. The outcomes of ANN shows good sign of correlation between material and product design domains. The study enriches a new path to illustrate material factors at the time of new product development.
Year
Venue
Keywords
2010
Clinical Orthopaedics and Related Research
product design,integration,material design,composition,mechanical properties,artificial neural network,network model,functional requirement,artificial intelligent,feed forward,computer simulation,new product development,back propagation
Field
DocType
Volume
Functional requirement,Data mining,Authentication,Industrial engineering,Computer science,Finite element method,Artificial intelligence,Material Design,Product design,Computational fluid dynamics,Network model,New product development
Journal
abs/1002.1
ISSN
Citations 
PageRank 
International Journal of Computer Science Issues, IJCSI, Vol. 7, Issue 1, No. 1, January 2010, http://ijcsi.org/articles/Establishment-of-Relationships-between-Material-Design-and-Product-Design-Domains-by-Hybrid-FEM-ANN-Technique.php
0
0.34
References 
Authors
1
3
Name
Order
Citations
PageRank
K. Soorya Prakash100.34
S. S. Mohamed Nazirudeen200.34
M. Joseph Malvin Raj300.34