Knowledge based design advisory system for multi-material joining. (July 2019)

• Record Type: Journal Article
• Authors: Kim, Ji Hoon; Wang, Lyang Suan; Putta, Kaushalya; Haghighi, Payam; Shah, Jami J.; Edwards, Pete
• Is Part Of: Journal of manufacturing systems. Volume 52(2019)Part B
• Page Start: 253
• Page End: 263
• Publication Date: 2019-07
• Subjects: Design advisory system -- Multi material joining -- Database -- Knowledge based advisory system; Manufacturing processes -- Periodicals; Production engineering -- Data processing -- Periodicals; Robots, Industrial -- Periodicals; Production, Technique de la -- Informatique -- Périodiques; Robots industriels -- Périodiques; Electronic journals; 670.42
• DOI: 10.1016/j.jmsy.2019.03.003
• Languages: English
• ISSNs: 0278-6125

Abstract

Abstract: Multi-Material Joining Design Explorer is discussed in this paper, which is a knowledge-based advisory system to help structural designers at the early design phase to select the potential joining methods. Data mining on various joining methods was conducted from any available sources, such as experts from academia and industry, handbooks, and vendors. Collected data was organized in a concept map which is an informal way of representing the data structure. The data were arranged into several categories according to their characteristics which include joinable materials, mechanical and design requirements, geometry, and so on. Common parameters and unique parameters were extracted from deep investigation of the gathered data to create a formalized data structure. A database using a general tree structure was then created to be fed into the advisory system. Searching algorithm using SQL query was implemented to navigate through the database to find the joining methods that match the requirements defined by the user. Two test cases were generated to validate the function of the knowledge-based system.