Paper Info
Title
Constructing manufacturing-environmental model in Bayesian belief networks for assembly design decision support through fuzzy cognitive maps
Abstract
This paper deals with the introduction of the Bayesian belief network (BBN) for the representation and reasoning about manufacturing environmental knowledge which captures the interactions between manufacturing-environmental factors and assembly design decision (ADD) criteria. BBN is used because it has a sound mathematical foundation, expressive representation scheme, powerful reasoning capability, efficient evidence propagation mechanism and proven track record in industry-scale applications. Unfortunately, the construction of conditional probability tables (CPTs) is both tedious and unnatural. Hence, fuzzy cognitive map (FCM) is introduced for knowledge acquisition because it is simple and user friendly. We also propose a method for the conversion of FCM into BBN.
Year
DOI
Venue
2009
10.1504/IJIIDS.2009.023035
IJIIDS
Keywords
Field
DocType
fuzzy cognitive map,manufacturing-environmental model,conditional probability table,powerful reasoning capability,efficient evidence propagation mechanism,assembly design decision support,industry-scale application,expressive representation scheme,assembly design decision,knowledge acquisition,bayesian belief network,environmental knowledge,decision support,fuzzy cognitive maps,bayesian belief networks,manufacturing
Cognitive map,Conditional probability,Computer science,Decision support system,Fuzzy logic,Fuzzy cognitive map,Bayesian network,Artificial intelligence,User Friendly,Knowledge acquisition,Machine learning
Journal
Volume
Issue
Citations 
3
1
4
PageRank 
References 
Authors
0.46
14
5
Name
Order
Citations
PageRank
Wooi Ping Cheah1368.03
Kyoung-Yun Kim221023.90
Hyungjeong Yang345547.05
Man-Sun Kim4121.77
Jeong-Sik Kim5135.58