Please use this identifier to cite or link to this item:
https://hdl.handle.net/1959.11/61815
Title: | Experience based decisional DNA to support smart product design |
Contributor(s): | Bilal Ahmed, Muhammad (author); Sanin, Cesar (author) ; Shafiq, Syed Imran (author); Szczerbicki, Edward (author) |
Publication Date: | 2019-12-23 |
DOI: | 10.3233/JIFS-179330 |
Handle Link: | https://hdl.handle.net/1959.11/61815 |
Abstract: | | This paper presents the idea of Smart Virtual Product Development (SVPD) system to support product design. The foundations of the system are based upon smart knowledge management techniques called Set of Experience Knowledge Structure (SOEKS) and Decisional DNA (DDNA). It enhances the industrial product development process by using the previous experiential knowledge gathered from the formal decisional activities. This experiential knowledge is collected from the group of similar products having some common functions and features. The developed system comprises of three modules: design knowledge management (DKM), manufacturing capability analysis and process planning (MCAPP), and product inspection planning (PIP). The working of design knowledge management module is presented in this study and is validated by using an industrial case study, which suggests that it is capable of capturing and reusing the required design knowledge for material selection process. The developed system has the capability to facilitate decision making and mistake proofing during early stages of product design. It can be beneficial for small and medium enterprises (SMEs) involved in product development.
Publication Type: | Journal Article |
Source of Publication: | Journal of Intelligent and Fuzzy Systems, 37(6), p. 7179-7187 |
Publisher: | IOS Press |
Place of Publication: | The Netherlands |
ISSN: | 1875-8967 1064-1246 |
Fields of Research (FoR) 2020: | 4602 Artificial intelligence |
Peer Reviewed: | Yes |
HERDC Category Description: | C1 Refereed Article in a Scholarly Journal |
Appears in Collections: | Journal Article School of Science and Technology
|
Files in This Item:
1 files
Show full item record
Items in Research UNE are protected by copyright, with all rights reserved, unless otherwise indicated.