Establishment of Relationships between Material Design and Product Design Domains by Hybrid FEM-ANN Technique

TL;DR

This paper presents a hybrid FEM-ANN approach to model and establish relationships between material design and product design, enhancing predictive capabilities for alloy development and product optimization.

Contribution

It introduces a novel AI-based modeling technique using ANN to connect material properties with product design parameters, facilitating better material selection and product development.

Findings

ANN shows strong correlation between material and product design domains

The approach enables prediction of product behavior based on material features

The method supports optimized alloy development for specific product requirements

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.