Full metadata record
DC FieldValueLanguage
dc.contributorDepartment of Industrial and Systems Engineeringen_US
dc.creatorQian, Chen-
dc.identifier.urihttps://theses.lib.polyu.edu.hk/handle/200/7524-
dc.languageEnglishen_US
dc.publisherHong Kong Polytechnic University-
dc.rightsAll rights reserveden_US
dc.titleProduction starting time control for compensating forecast error and customer loss in waitingen_US
dcterms.abstractProduction systems play a key role in modern society, and significant improvements have been achieved through the years. However, due to the diversity of human behavior, customer demand uncertainty does exist in practice. Consequently, production solutions that are capable of coping with such diverse behavior are necessary. To have a better competitive position, forecasting is an important element in production management. Thus, there is always research for improving forecasting accuracy and the development of new methods is on-going. Apart from working on new forecast methods or improving existing models, this research focused on working with the expected forecast error in a most economical way. To achieve this goal, the aim was to achieve a balance between the effect of forecast error with time and the customer loss in the waiting period. In this research, a production approach named Make-to-Balance (MTB) is introduced. To verify the concept and the operating result of the proposed model, a simulation process was built with STELLA, and a software program was also coded in C# language. The SETLLA results and program results match well in different situations (one general case and four extreme cases) and identify the correctness of the MTB model. The program eases the calculations and it was found in this research that the optimal solution could be obtained from MTB and Smart-MTB version programs. Indeed, the contributions of this research are not only in its inspirations but also in that it extends the view on how to run a production system effectively by taking uncertainty and customer behavior into account, and it also shows that customer loyalty helps to reduce the effect on forecast error.en_US
dcterms.extentviii, 146 leaves : illustrations (some color) ; 30 cmen_US
dcterms.isPartOfPolyU Electronic Thesesen_US
dcterms.issued2014en_US
dcterms.educationalLevelAll Doctorateen_US
dcterms.educationalLevelPh.D.en_US
dcterms.LCSHHong Kong Polytechnic University -- Dissertationsen_US
dcterms.LCSHProduction management.en_US
dcterms.LCSHProduction management -- Data processing.en_US
dcterms.accessRightsopen accessen_US

Files in This Item:
File Description SizeFormat 
b27575287.pdfFor All Users2.94 MBAdobe PDFView/Open


Copyright Undertaking

As a bona fide Library user, I declare that:

  1. I will abide by the rules and legal ordinances governing copyright regarding the use of the Database.
  2. I will use the Database for the purpose of my research or private study only and not for circulation or further reproduction or any other purpose.
  3. I agree to indemnify and hold the University harmless from and against any loss, damage, cost, liability or expenses arising from copyright infringement or unauthorized usage.

By downloading any item(s) listed above, you acknowledge that you have read and understood the copyright undertaking as stated above, and agree to be bound by all of its terms.

Show simple item record

Please use this identifier to cite or link to this item: https://theses.lib.polyu.edu.hk/handle/200/7524