Function Block Based Real-Time Tool Path Optimisation

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dc.contributor.advisor Mehnen, Jorn
dc.contributor.advisor Fan, Ip-Shing
dc.contributor.author Guo, Xixuan
dc.date.accessioned 2015-06-15T15:02:55Z
dc.date.available 2015-06-15T15:02:55Z
dc.date.issued 2014-09
dc.identifier.uri http://dspace.lib.cranfield.ac.uk/handle/1826/9246
dc.description.abstract With the changing and increasingly more demanding global markets, also Computer Aided Process Planning (CAPP) gets challenged. Industry is expecting more adaptive, dynamic, intelligent CAPP systems to deal with the uncertainty and the increasing complexity of machining processes. Generally, high intelligence and automation are the tendency of industry. Conventional CAPP systems as well as off-line optimisation have been very well investigated over many years. However, well-optimised solutions developed for static environments still often need manual manipulation when dealing with uncertainty and dynamics. As one of the emerging software technologies, Function Blocks have been introduced to deal with uncertainty in CAPP and manufacturing. The underlying hypothesis of this research is that Function Blocks delivered through the Cloud and deployed into a milling machine controller can provide real-time monitoring, optimisation and control. In this study, a real-time Function Blocks based tool path optimisation for face milling system is proposed. The system can optimise feed rate and cutting speed to create stable cutting conditions in real-time based on measured dynamically fluctuating cutting forces. en_UK
dc.language.iso en en_UK
dc.publisher Cranfield University en_UK
dc.rights © Cranfield University 2013. All rights reserved. No part of this publication may be reproduced without the written permission of the copyright own en_UK
dc.title Function Block Based Real-Time Tool Path Optimisation en_UK
dc.type Thesis or dissertation en_UK
dc.type.qualificationlevel Masters en_UK
dc.type.qualificationname MSc by Research en_UK


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