An industry 4.0-enabled low cost predictive maintenance approach for SMEs: a use case applied to a CNC turning centre

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dc.contributor.authorSezer, Erim
dc.contributor.authorRomero, David
dc.contributor.authorGuedea, Federico
dc.contributor.authorMacchi, Marco
dc.contributor.authorEmmanouilidis, Christos
dc.date.accessioned2019-03-26T15:44:36Z
dc.date.available2019-03-26T15:44:36Z
dc.date.issued2018-08-16
dc.description.abstractThis paper outlines the base concepts, materials and methods used to develop an Industry 4.0 architecture focused on predictive maintenance, while relying on low-cost principles to be affordable by Small Manufacturing Enterprises. The result of this research work was a low-cost, easy-to-develop cyber-physical system architecture that measures the temperature and vibration variables of a machining process in a Haas CNC turning centre, while storing such data in the cloud where Recursive Partitioning and Regression Tree model technique is run for predicting the rejection of machined parts based on a quality threshold. Machining quality is predicted based on temperature and/or vibration machining data and evaluated against average surface roughness of each machined part, demonstrating promising predictive accuracy.en_UK
dc.identifier.citationErim Sezer, David Romero, Federico Guedea, et al., An industry 4.0-enabled low cost predictive maintenance approach for SMEs: a use case applied to a CNC turning centre. 2018 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC), 17-20 June 2018, Stuttgart, Germanyen_UK
dc.identifier.isbn978-1-5386-1469-3
dc.identifier.urihttps://doi.org/ 10.1109/ICE.2018.8436307
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/14010
dc.language.isoenen_UK
dc.publisherIEEEen_UK
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.subjecte-Maintenanceen_UK
dc.subjectPredictive Maintenanceen_UK
dc.subjectCondition Based Maintenanceen_UK
dc.subjectIndustry 4.0en_UK
dc.subjectSmart Manufacturingen_UK
dc.subjectMachine Learningen_UK
dc.subjectSmall Manufacturing Enterpriseen_UK
dc.subjectLow Costen_UK
dc.subjectOpen Sourceen_UK
dc.titleAn industry 4.0-enabled low cost predictive maintenance approach for SMEs: a use case applied to a CNC turning centreen_UK
dc.typeConference paperen_UK

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