Artificial Neural Networks to Optimize the Conceptual Design of Adaptable Product Development

Date published

2009-03-31

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Supervisor/s

Journal Title

Journal ISSN

Volume Title

Publisher

Cranfield University Press

Department

Type

Conference paper

ISSN

Format

Citation

J. Feldhusen, A. Nagarajah, Artificial Neural Networks to Optimize the Conceptual Design of Adaptable Product Development, Proceedings of the 19th CIRP Design Conference – Competitive Design, Cranfield University, 30-31 March 2009, pp51

Abstract

This paper describes an approach to apply Artificial Neural Network (ANN) to support the developer to optimize the conceptual design of Adaptable Product Development. The ANN learn from the previously mapping between the requirements and the product solutions. For a new development Process of an Adaptable Product the ANN analyse existing solution and sort them according to their probability of success. The advantages of this approach is on the one hand that ANN is able to identify the best suitable product solution for a new development order and on other hand the ANN automatically store the knowledge of the developer.

Description

Organised by: Cranfield University

Software Description

Software Language

Github

Keywords

Product Development Process, Engineering Design, Neural Network, Adaptable Products

DOI

Rights

Copyright: Cranfield University 2009

Relationships

Relationships

Supplements

Funder/s

Mori Seiki – The Machine Tool Company