Design knowledge extraction from scenario-based databases using associative search engine for FR-induced decisions

• Published in: CIRP annals Vol. 57; no. 1; pp. 163 - 166
• Main Authors: Nakao, M., Tsuchiya, K., Iino, K.
• Format: Journal Article Conference Proceeding
• Language: English
• Published: Oxford Elsevier Ltd 2008; Elsevier
• Subjects: Applied sciences; Computer science; control theory; systems; Decision making; Decision theory. Utility theory; Design method; Exact sciences and technology; Information systems. Data bases; Knowledge management; Memory organisation. Data processing; Operational research and scientific management; Operational research. Management science; Software; Design method; Decision making; Knowledge management; Knowledge engineering; Script; Decision support system; Search engine; Rupture; Functional analysis; Knowledge base; Failures; Knowledge extraction; Accident; Database; Knowledge discovery
• ISSN: 0007-8506
• DOI: 10.1016/j.cirp.2008.03.050

The authors set the functional requirement of “reduce your own risk” and ran sessions of associative search to extract useful knowledge from databases. Ninety engineers found the most analogous knowledge using the associative search engine “GETA/IMAGINE” on scenario-based databases “Failure Knowledge Database” and “100 Scenarios of Failure.” Above 60% of their risk concern cases successfully reached the most analogous accident cases or failure scenarios from either database in about 10
min. Associative search can aid the designer in selecting design solutions for the functional domain.