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Artificial intelligence methods for improving the inventive design process, application in lattice structure case study

Published online by Cambridge University Press:  18 July 2022

Masih Hanifi Open the ORCID record for Masih Hanifi [Opens in a new window] ,
Hicham Chibane Open the ORCID record for Hicham Chibane [Opens in a new window] ,
Remy Houssin ,
Denis Cavallucci  and
Naser Ghannad
Masih Hanifi*
Affiliation:
Strasbourg University, 4 Rue Blaise Pascal, 67081 Strasbourg, France INSA of Strasbourg, 24 Boulevard de la Victoire, 67000 Strasbourg, France
Hicham Chibane
Affiliation:
INSA of Strasbourg, 24 Boulevard de la Victoire, 67000 Strasbourg, France
Remy Houssin
Affiliation:
Strasbourg University, 4 Rue Blaise Pascal, 67081 Strasbourg, France
Denis Cavallucci
Affiliation:
INSA of Strasbourg, 24 Boulevard de la Victoire, 67000 Strasbourg, France
Naser Ghannad
Affiliation:
INSA of Strasbourg, 24 Boulevard de la Victoire, 67000 Strasbourg, France
*
Author for correspondence: Masih Hanifi, E-mail: [email protected]
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Abstract

Nowadays, firms are constantly looking for methodological approaches that help them to decrease the time needed for the innovation process. Among these approaches, it is worth mentioning the TRIZ-based frameworks such as the Inventive Design Methodology (IDM), where the Problem Graph method is used to formulate a problem. However, the application of IDM is time-consuming due to the construction of a complete map to clarify a problem situation. Therefore, the Inverse Problem Graph (IPG) method has been introduced within the IDM framework to enhance its agility. Nevertheless, the manual gathering of essential information, including parameters and concepts, requires effort and time. This paper integrates the neural network doc2vec and machine learning algorithms as Artificial Intelligence methods into a graphical method inspired by the IPG process. This integration can facilitate and accelerate the development of inventive solutions by extracting parameters and concepts in the inventive design process. The method has been applied to develop a new lattice structure solution in the material field.

Keywords

Artificial intelligencedocument embeddinginventive designlattice structuresimilarity computationtext classification
Type
Research Article
Information
AI EDAM , Volume 36 , 2022 , e20
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Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press

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