Lead time predictions for a job shop

dc.contributor.authorYu, Wei-Shinen
dc.date.accessioned2011-12-14T22:48:40Z
dc.date.available2011-12-14T22:48:40Z
dc.date.issued1975en
dc.description.abstractFor a job shop, there has been very little research done on the accurate prediction of lead times, despite of the importance of and the advantages to be gained from the ability to predict lead times accurately. In job shop scheduling using integer programming method, etc., to produce fixed schedules, the lead time estimates can be obtained directly from the schedules. But none of these methods is of any appreciable use to industry. Heuristic job shop scheduling, on the other hand, has been implemented and performs satisfactorily. However, the means of predicting the lead times has to be formulated separately. This work investigates existing methods of predicting lead times, for a job shop employing heuristic scheduling. It evaluates their stability, system response rates, and their accuracy under steady state conditions. Before a method can be implemented for a real life job shop, it must be tested under dynamic conditions extensively, and found to be stable. The accuracy of the lead time predicted under such condition, must also be acceptable. Hence, the method with the best accuracy from the evaluation was subjected to such dynamic tests. The results of the tests showed that this method was stable under all the dynamic conditions tested, and predicted lead time with very good accuracy. A new version of this method is formulated. Testing under similar steady state and dynamic conditions, showed that it was superior to the version.en
dc.identifier.urihttp://hdl.handle.net/10092/6058
dc.identifier.urihttp://dx.doi.org/10.26021/2466
dc.language.isoen
dc.publisherUniversity of Canterbury. Mechanical Engineeringen
dc.relation.isreferencedbyNZCUen
dc.rightsCopyright Wei-Shin Yuen
dc.rights.urihttps://canterbury.libguides.com/rights/thesesen
dc.titleLead time predictions for a job shopen
dc.typeTheses / Dissertations
thesis.degree.grantorUniversity of Canterburyen
thesis.degree.levelDoctoralen
thesis.degree.nameDoctor of Philosophyen
uc.bibnumber49500
uc.collegeFaculty of Engineeringen
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