{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/132888"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/132888","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Digitalizing R&D in manufacturing sector : machine learning, infrastructure, system architecture and knowledge management","abstract":"This thesis addresses the topic of data utilization and data analytics in research and development (R&D) functions of the manufacturing sector. Many companies in the manufacturing sector have generated significant quantities of data in their histories, but only a tiny part of these data is utilized. With the significant progress in big data analytics and machine learning, the companies in the manufacturing sector are able to upgrade their R&D capability by establishing a system to better collect and analyze their data. 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