A framework to manage uncertainties in cloud manufacturing environment

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dc.contributor.advisor Shehab, Essam
dc.contributor.advisor Mehnen, Jorn
dc.contributor.author Yadekar, Yaser
dc.date.accessioned 2017-09-13T10:37:15Z
dc.date.available 2017-09-13T10:37:15Z
dc.date.issued 2016-10
dc.identifier.uri http://dspace.lib.cranfield.ac.uk/handle/1826/12477
dc.description.abstract This research project aims to develop a framework to manage uncertainty in cloud manufacturing for small and medium enterprises (SMEs). The framework includes a cloud manufacturing taxonomy; guidance to deal with uncertainty in cloud manufacturing, by providing a process to identify uncertainties; a detailed step-by-step approach to managing the uncertainties; a list of uncertainties; and response strategies to security and privacy uncertainties in cloud manufacturing. Additionally, an online assessment tool has been developed to implement the uncertainty management framework into a real life context. To fulfil the aim and objectives of the research, a comprehensive literature review was performed in order to understand the research aspects. Next, an uncertainty management technique was applied to identify, assess, and control uncertainties in cloud manufacturing. Two well-known approaches were used in the evaluation of the uncertainties in this research: Simple Multi-Attribute Rating Technique (SMART) to prioritise uncertainties; and a fuzzy rule-based system to quantify security and privacy uncertainties. Finally, the framework was embedded into an online assessment tool and validated through expert opinion and case studies. Results from this research are useful for both academia and industry in understanding aspects of cloud manufacturing. The main contribution is a framework that offers new insights for decisions makers on how to deal with uncertainty at adoption and implementation stages of cloud manufacturing. The research also introduced a novel cloud manufacturing taxonomy, a list of uncertainty factors, an assessment process to prioritise uncertainties and quantify security and privacy related uncertainties, and a knowledge base for providing recommendations and solutions. en_UK
dc.language.iso en en_UK
dc.publisher Cranfield University en_UK
dc.rights © Cranfield University, 2016. All rights reserved. No part of this publication may be reproduced without the written permission of the copyright holder. en_UK
dc.subject Cloud Technology en_UK
dc.subject Cloud Manufacturing en_UK
dc.subject Cloud Computing en_UK
dc.subject Uncertainty en_UK
dc.subject Uncertainty Management en_UK
dc.subject Simple Multi-Attribute Rating Technique en_UK
dc.subject Fuzzy rule-based system en_UK
dc.title A framework to manage uncertainties in cloud manufacturing environment en_UK
dc.type Thesis or dissertation en_UK
dc.type.qualificationlevel Doctoral en_UK
dc.type.qualificationname PhD en_UK

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