Sustainability of quality improvement programmes in a heavy engineering manufacturing environment : a system dynamics approach

dc.contributor.advisorPretorius, Leon
dc.contributor.emaildirk.vandyk@joyglobal.com
dc.contributor.postgraduateVan Dyk, Johannes Dirk
dc.date.accessioned2013-11-12T06:34:30Z
dc.date.available2013-11-12T06:34:30Z
dc.date.created2013-09-04
dc.date.issued2013
dc.descriptionThesis (PhD)--University of Pretoria, 2013.en_US
dc.description.abstractCompanies realize to stay competitive they have to introduce quality improvement programs. Many companies are challenged today with the sustainability of these quality improvement programs. Generally the understanding of the dynamic behaviour of quality improvement programs is poorly understood with soft issues as factors of the system. System dynamics may solve this problem. This research was focussed on operational management of operations. The organising framework of this research has been qualitative research where the research design was a polar type research design where the case studies focussed on initiatives that were dramatic success or failures, with the expectation that their comparison would help identify those processes that prevent competence enhancing change. A dynamic hypothesis has been constructed from archival data, semi-structured interviews and direct observations, gathered during these case studies. A system dynamics model for quality improvement programs in an automotive environment has been tested and expanded to be applicable for a heavy engineering manufacturing environment. The structure of the system dynamics model has been expanded to include a sustainability feedback loop which also included a management support model. The management support model included soft factors such as management support, management pressure and managerial effectiveness. The complete quality improvement program system dynamics simulation model with sustainability has been tested and validated against a real system data, for a heavy engineering manufacturing environment, gathered during the case studies. The model parameters were determined from a calibration algorithm, by using the Vensim® simulation platform, that fitted the real system behaviour the best. A sensitivity analysis has been done on the model parameters determining the information cues for the management decision policies. From the system dynamics model of the complete quality improvement program, including the sustainability feedback loop, proposed management decision policies have been studied that could lead to sustainable quality improvement programs for a heavy engineering manufacturing environment. From these simulation studies several management policies have been proposed.en_US
dc.description.availabilityUnrestricteden_US
dc.description.departmentGraduate School of Technology Management (GSTM)en_US
dc.description.librariangm2013en_US
dc.identifier.citationVan Dyk, DJ 2013, Sustainability of quality improvement programmes in a heavy engineering manufacturing environment : a system dynamics approach, PhD thesis, University of Pretoria, Pretoria, viewed yymmdd <http://hdl.handle.net/2263/32369>en_US
dc.identifier.otherD13/9/1044/gmen_US
dc.identifier.urihttp://hdl.handle.net/2263/32369
dc.language.isoenen_US
dc.publisherUniversity of Pretoriaen_ZA
dc.rights© 2013 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria.en_US
dc.subjectQuality improvement programmesen_US
dc.subjectManufacturing environmenten_US
dc.subjectSystem dynamics approachen_US
dc.subjectSustainabilityen_US
dc.subjectOperational managementen_US
dc.subjectAutomotive environmenten_US
dc.subjectManagerial effectivenessen_US
dc.subjectManagement supporten_US
dc.subjectVensim® simulation platformen_US
dc.subjectUCTDen_US
dc.titleSustainability of quality improvement programmes in a heavy engineering manufacturing environment : a system dynamics approachen_US
dc.typeThesisen_US

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