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dc.contributor.authorKeprate, Arvind
dc.contributor.authorChatterjee, Supratik
dc.date.accessioned2022-03-31T07:52:26Z
dc.date.available2022-03-31T07:52:26Z
dc.date.created2022-01-25T12:00:30Z
dc.date.issued2021-01-20
dc.identifier.isbn978-1-6654-3771-4
dc.identifier.isbn978-1-6654-3772-1
dc.identifier.issn2157-3611
dc.identifier.urihttps://hdl.handle.net/11250/2988712
dc.description.abstractIn the recent years, industries such as aeronautical, railway, and petroleum has transitioned from corrective/preventive maintenance to condition based maintenance (CBM). One of the enablers of CBM is Prognostics which primarily deals with prediction of remaining useful life of an engineering asset. Besides physics-based approaches, data driven methods are widely used for prognostics purposes, however the latter technique requires availability of run to failure datasets. In this manuscript authors have aimed at performing exploratory data analysis (EDA) on the New Commercial Modular Aero-Propulsion System Simulation (N-CMAPSS) dataset published by NASA. Although 8 datasets are publicly available, authors have chosen dataset 3 (DS03) for EDA in this paper which consists of 9.8 million instances and 47 features. The main aim of doing EDA is to gain better understanding of the dataset as it would facilitate in building a deep learning model that can be used for predicting RUL of the aircraft engines.en_US
dc.language.isoengen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.relation.ispartofseriesIEEE International Conference on Industrial Engineering and Engineering Management;2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)
dc.subjectPrognosticsen_US
dc.subjectExploratory data analysesen_US
dc.subjectN-CMAPSS datasetsen_US
dc.subjectNew commercial modular aero-propulsion system simulation datasetsen_US
dc.titleExploratory Data Analysis of the N-CMAPSS Dataset for Prognosticsen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionacceptedVersionen_US
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.fulltextoriginal
cristin.qualitycode1
dc.identifier.doihttps://doi.org/10.1109/IEEM50564.2021.9673064
dc.identifier.cristin1989373
dc.source.journalIEEE International Conference on Industrial Engineering and Engineering Managementen_US
dc.source.volume15en_US
dc.source.issue15en_US
dc.source.pagenumber8en_US


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