Content area

Abstract

The process of product design specification is subjective in nature and this motivates the application of approaches and methods to make it explicit. Among the available approaches, the systematization of the development of a single product, modular products, family of products and products for mass customization stands out. Among the methods, the design structure matrix (DSM) is highlighted, as well as the use of networks to represent the variables and their interdependence relations. Representation is very important to increase the cognitive capacity of those involved in the design and to facilitate communication between specialists and non-specialists. The clarification of the knowledge and reasoning of the design increases the complexity of the specification, which needs to be managed. In this work, the method called design structure network (DSN) is proposed, allowing the visualization of the design variables as nodes of a network and the relations of interdependence as links and the specification reasoning can be represented as a path that connects the nodes in a network. For the management of network complexity, ten principles based on cognitive processes are implemented. The DSN method was applied in the geometric specification of surfboard, and the results obtained show the potential of graphical representation of the specification reasoning, as well as the ability to reduce the complexity of the network.

Details

Title
Design structure network (DSN): a method to make explicit the product design specification process for mass customization
Author
Loureiro Guilherme Branco 1 ; Ferreira Joao Carlos Espindola 1   VIAFID ORCID Logo  ; Messerschmidt Paulo Henrique Zen 1 

 Universidade Federal de Santa Catarina, Florianópolis, Brazil (GRID:grid.411237.2) (ISNI:0000 0001 2188 7235) 
Pages
197-220
Publication year
2020
Publication date
Apr 2020
Publisher
Springer Nature B.V.
ISSN
09349839
e-ISSN
14356066
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2386673365
Copyright
© Springer-Verlag London Ltd., part of Springer Nature 2020.