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Article: Application of a hybrid case-based reasoning approach in electroplating industry

TitleApplication of a hybrid case-based reasoning approach in electroplating industry
Authors
KeywordsArtificial intelligence
Case-based reasoning
Electroplating industry
Fuzzy logic
Rule-based reasoning
Issue Date2005
PublisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/eswa
Citation
Expert Systems With Applications, 2005, v. 29 n. 1, p. 121-130 How to Cite?
AbstractCase-Based Reasoning (CBR), a well known Artificial Intelligence (AI) technique, has already proven its effectiveness in numerous industries. In this research, we try to adopt CBR technique in electroplating industry where the final products are electroplated accessory of watches. In order to ensure sufficient profit margin for electroplating manufacturer, it is important to grasp the coating weight of electroplating component accurately so that salespersons can make sure their quotation prices cover the precious metal cost. Apart from quotation accuracy, responsiveness is also a critical competitive edge in electroplating industry. In this connection, developing a quick response decision-making system with considerably reliable price is what electroplating industry needs. To cope with this problem, a hybrid CBR system combined with Rule-based Reasoning (RBR) and Fuzzy Logic (FL) concepts is established. Such system is capable to convert knowledge from experienced staff; simulate the 'mind-set' of decision maker in solving problem through acquisition of specific knowledge and experience; and build up self-learning characteristics. Moreover, this research interprets cases as some objective selection rules, putting CBR in a position much closer to RBR. This innovative concept differentiates from previous CBR researcher work, and will be explained through a practical example. Further, this research also suggested that it is very difficult and not practical to develop a pure CBR system. Applying some subjective guiding rules in CBR can significantly improve the performance of system in the early learning stage. © 2005 Elsevier Ltd. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/74519
ISSN
2015 Impact Factor: 2.981
2015 SCImago Journal Rankings: 1.839
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorChan, FTSen_HK
dc.date.accessioned2010-09-06T07:02:07Z-
dc.date.available2010-09-06T07:02:07Z-
dc.date.issued2005en_HK
dc.identifier.citationExpert Systems With Applications, 2005, v. 29 n. 1, p. 121-130en_HK
dc.identifier.issn0957-4174en_HK
dc.identifier.urihttp://hdl.handle.net/10722/74519-
dc.description.abstractCase-Based Reasoning (CBR), a well known Artificial Intelligence (AI) technique, has already proven its effectiveness in numerous industries. In this research, we try to adopt CBR technique in electroplating industry where the final products are electroplated accessory of watches. In order to ensure sufficient profit margin for electroplating manufacturer, it is important to grasp the coating weight of electroplating component accurately so that salespersons can make sure their quotation prices cover the precious metal cost. Apart from quotation accuracy, responsiveness is also a critical competitive edge in electroplating industry. In this connection, developing a quick response decision-making system with considerably reliable price is what electroplating industry needs. To cope with this problem, a hybrid CBR system combined with Rule-based Reasoning (RBR) and Fuzzy Logic (FL) concepts is established. Such system is capable to convert knowledge from experienced staff; simulate the 'mind-set' of decision maker in solving problem through acquisition of specific knowledge and experience; and build up self-learning characteristics. Moreover, this research interprets cases as some objective selection rules, putting CBR in a position much closer to RBR. This innovative concept differentiates from previous CBR researcher work, and will be explained through a practical example. Further, this research also suggested that it is very difficult and not practical to develop a pure CBR system. Applying some subjective guiding rules in CBR can significantly improve the performance of system in the early learning stage. © 2005 Elsevier Ltd. All rights reserved.en_HK
dc.languageengen_HK
dc.publisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/eswaen_HK
dc.relation.ispartofExpert Systems with Applicationsen_HK
dc.subjectArtificial intelligenceen_HK
dc.subjectCase-based reasoningen_HK
dc.subjectElectroplating industryen_HK
dc.subjectFuzzy logicen_HK
dc.subjectRule-based reasoningen_HK
dc.titleApplication of a hybrid case-based reasoning approach in electroplating industryen_HK
dc.typeArticleen_HK
dc.identifier.emailChan, FTS: ftschan@hkucc.hku.hken_HK
dc.identifier.authorityChan, FTS=rp00090en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.eswa.2005.01.010en_HK
dc.identifier.scopuseid_2-s2.0-16244364814en_HK
dc.identifier.hkuros100475en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-16244364814&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume29en_HK
dc.identifier.issue1en_HK
dc.identifier.spage121en_HK
dc.identifier.epage130en_HK
dc.identifier.isiWOS:000228843300011-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridChan, FTS=7202586517en_HK

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