Nandi, A.K. and Deb, K. and Datta, S. (2013) Genetic Algorithm–Based Design and Development of Particle-Reinforced Silicone Rubber for Soft Tooling Process. Materials and Manufacturing Processes, 28. pp. 753-760. ISSN 1042-6914

Full text not available from this repository.

Abstract

In order to enhance the solidification rate of soft tooling process, design of a silicone rubber composite mold material is carried out based on multiobjective optimization (MOO) of conflicting objectives. The elitist nondominated sorting genetic algorithm (NSGA-II), a genetic algorithm–based MOO tool, is used to find the optimum parameters first by obtaining the Pareto-optimal front and then selecting a single solution or a small set of solutions for manufacturing applications using a suitable multi-criterion decision making technique. Based on the optimal design parameters, an experimental study in soft tooling process is carried out in particle-reinforced silicone, and it is observed that the solidification time is minimized appreciably keeping the same advantages of soft tooling process.

Item Type:	Article
Subjects:	Soft tooling
Depositing User:	Dr. Sarita Ghosh
Date Deposited:	06 Apr 2016 03:46
Last Modified:	06 Apr 2016 03:46
URI:	http://cmeri.csircentral.net/id/eprint/83

Actions (login required)

View Item