Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/13487
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dc.contributor.authorSim, Norman Boon Heng.en_US
dc.date.accessioned2008-10-20T08:20:40Z-
dc.date.available2008-10-20T08:20:40Z-
dc.date.copyright1999en_US
dc.date.issued1999en_US
dc.identifier.urihttp://hdl.handle.net/10356/13487-
dc.description.abstractUntil today, the term Computer Integrated Manufacturing (CIM) has been so commonly used that it is on the brink of falling into the 'buzzword vocabulary well' of the manufacturing arena is very high. CIM, however, has the potential of materializing the vision of continuous improvement. Statistical Process Control (SPC), a highly sought after Total Quality Control tool in the 1980's, is today part and parcel of manufacturing. Together with the concept of SPC, which has time and again been proven to be a simple but yet an effective method of reducing variation, CIM can facilitate the continuous improvement process. The traditional control charts used in detecting variation in a particular characteristic (and hence, process variation) may not be applicable for process monitoring in a CIM environment. Control charts and the manner in which data is to be collected need to be modified to suit the various aspects of automation in CIM including automated data collection.en_US
dc.format.extent95 p.en_US
dc.language.isoenen_US
dc.subjectDRNTU::Engineering::Manufacturing::Quality controlen_US
dc.titleIntegrating statistical process control and enterprise resource planning systems in a computer integrated manufacturing environmenten_US
dc.typeThesisen_US
dc.contributor.supervisorSpedding, Trevor Allanen_US
dc.contributor.schoolSchool of Mechanical and Production Engineeringen_US
dc.description.degreeMaster of Science (Computer Integrated Manufacturing)en_US
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