Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/19883
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dc.contributor.authorKhaw, Fook Cheon.en_US
dc.date.accessioned2009-12-14T07:05:01Z-
dc.date.available2009-12-14T07:05:01Z-
dc.date.copyright1994en_US
dc.date.issued1994-
dc.identifier.urihttp://hdl.handle.net/10356/19883-
dc.description.abstractGroup Technology (GT) concept has widely been adopted in many manufacturing companies. In these companies, the required resources including the machines, tooling and material handling equipment dedicated for each part family are grouped into a GT cell. Such an arrangement will enable the manufacturing companies to simplify their scheduling processes. To-date many scheduling heuristics have been developed to improve the effectiveness of scheduling in the GT cells. These heuristics, however, have not been effective for scheduling parallel machines with major and minor setup times. Such machines can perform a variety of operations on a large set of part families. The determination of major and minor setup times for each machine is dependent on the similarities of part families to be scheduled on that machine. The objective is to minimize flow time and tardiness by reducing the total setup times.en_US
dc.format.extent270 p.-
dc.language.isoen-
dc.rightsNANYANG TECHNOLOGICAL UNIVERSITYen_US
dc.subjectDRNTU::Engineering::Systems engineering-
dc.titleAn integrated neural network based system and methodology for group technology schedulingen_US
dc.typeThesisen_US
dc.contributor.supervisorLim, Enk Ng Lennieen_US
dc.contributor.schoolSchool of Mechanical and Production Engineeringen_US
dc.description.degreeDoctor of Philosophy (MPE)en_US
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