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dc.contributor.authorWang, Chih-Hsuanen_US
dc.contributor.authorWu, Hui-Shanen_US
dc.date.accessioned2017-04-21T06:56:47Z-
dc.date.available2017-04-21T06:56:47Z-
dc.date.issued2016-04en_US
dc.identifier.issn0956-5515en_US
dc.identifier.urihttp://dx.doi.org/10.1007/s10845-013-0863-6en_US
dc.identifier.urihttp://hdl.handle.net/11536/133456-
dc.description.abstractA programmable logic controller (PLC) is a real-time system operated in severe conditions such as high/low temperatures or tough environments with excessive electrical noise. In particular, a PLC is designed to connect and control multiple mechatronic devices such as facility sensors and actuators and thus the issue of selecting/assessing PLC suppliers is critically important to achieve automatic process control and facility monitoring. In reality, various MCDM (multi-criteria decision making) composed of MADM (multi-attribute) and MODM (multi-objective) based schemes are frequently adopted to tackle the problem of supplier selection. Nevertheless, most of them have the following demerits: (1) the causal dependences between main criteria (or associate attributes) are rarely considered (2) a large number of pairwise comparisons are usually required to conduct the evaluation process. Consequently, a novel framework combining fuzzy DEMATEL, fuzzy AHP, with fuzzy Delphi is proposed to overcome the aforementioned shortcomings. Without requiring tedious pairwise comparisons, the importance weights of main criteria (associated attributes) and the performance scores of PLC vendors are systematically fused into the whole evaluation process. Furthermore, an industrial example is demonstrated to assist PLC practitioners in assessing the top three suppliers, such as SIEMENS (31 %), Allen-Bradley (22 %) and Mitsubishi (13 %).en_US
dc.language.isoen_USen_US
dc.subjectPLC evaluationen_US
dc.subjectMCDMen_US
dc.subjectFuzzy AHPen_US
dc.subjectFuzzy DEMATELen_US
dc.subjectFuzzy Delphien_US
dc.titleA novel framework to evaluate programmable logic controllers: a fuzzy MCDM perspectiveen_US
dc.identifier.doi10.1007/s10845-013-0863-6en_US
dc.identifier.journalJOURNAL OF INTELLIGENT MANUFACTURINGen_US
dc.citation.volume27en_US
dc.citation.issue2en_US
dc.citation.spage315en_US
dc.citation.epage324en_US
dc.contributor.department工業工程與管理學系zh_TW
dc.contributor.departmentDepartment of Industrial Engineering and Managementen_US
dc.identifier.wosnumberWOS:000372173800003en_US
Appears in Collections:Articles