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dc.contributor.authorScrimieri, Daniele
dc.contributor.authorOates, R.F.
dc.contributor.authorRatchev, S.M.
dc.date.accessioned2020-03-04T16:54:59Z
dc.date.accessioned2020-03-13T16:28:46Z
dc.date.available2020-03-04T16:54:59Z
dc.date.available2020-03-13T16:28:46Z
dc.date.issued2015-12
dc.identifier.citationScrimieri D, Oates RF and Ratchev SM (2015) Learning and reuse of engineering ramp-up strategies for modular assembly systems. Journal of Intelligent Manufacturing. 26: 1063-1076.en_US
dc.identifier.urihttp://hdl.handle.net/10454/17724
dc.descriptionYesen_US
dc.description.abstractWe present a decision-support framework for speeding up the ramp-up of modular assembly systems by learning from past experience. Bringing an assembly system to the expected level of productivity requires engineers performing mechanical adjustments and changes to the assembly process to improve the performance. This activity is time-consuming, knowledge-intensive and highly dependent on the skills of the engineers. Learning the ramp-up process has shown to be effective for making progress faster. Our approach consists of automatically capturing information about the changes made by an operator dealing with disturbances, relating them to the modular structure of the machine and evaluating the resulting system state by analysing sensor data. The feedback thus obtained on applied adaptations is used to derive recommendations in similar contexts. Recommendations are generated with a variant of the k-nearest neighbour algorithm through searching in a multidimensional space containing previous system states. Applications of the framework include knowledge transfer among operators and machines with overlapping structure and functionality. The application of our method in a case study is discussed.en_US
dc.description.sponsorshipFunded by the European Commission as part of the 7th Framework Program under the Grant agreement CP-FP 229208-2, FRAME project.en_US
dc.language.isoenen_US
dc.rights© Springer Science+Business Media New York 2013. Reproduced in accordance with the publisher's self-archiving policy. The final publication is available at Springer via https://doi.org/10.1007/s10845-013-0839-6.en_US
dc.subjectModular assembly systemsen_US
dc.subjectRamp-upen_US
dc.subjectDecision supporten_US
dc.subjectLearningen_US
dc.subjectClassificationen_US
dc.titleLearning and reuse of engineering ramp-up strategies for modular assembly systemsen_US
dc.status.refereedYesen_US
dc.date.Accepted2013-10-03
dc.date.application2013-10-18
dc.typeArticleen_US
dc.type.versionAccepted manuscripten_US
dc.identifier.doihttps://doi.org/10.1007/s10845-013-0839-6
dc.date.updated2020-03-04T16:55:05Z
refterms.dateFOA2020-03-13T16:29:29Z


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