Using lean manufacturing and machine learning for improving medicines procurement and dispatching in a hospital

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dc.contributor.advisorhttps://orcid.org/0000-0001-6013-2222
dc.contributor.authorJORDON, KAIO
dc.contributor.authorDOSSOU, PAUL-ERIC
dc.contributor.authorJoão Chang Junior
dc.date.accessioned2021-11-03T21:42:32Z
dc.date.available2021-11-03T21:42:32Z
dc.date.issued2019-06-05
dc.description.abstractIndustry 4.0 concepts are defined around the use of new technologies for improving industrial companies according to scientific, technological and organizational aspects. Enterprise complex problems could be solved in this frame. Many methods and concepts presented in the literature are focused on these aspects. A new method is being developed in Icam Paris-Sénart around the idea that sustainability must be the kernel of “industry of the future”. Indeed, the framework proposed is a combination of the previous aspects with environmental, social and societal aspects. The actual situation of the planet is an encouragement to make all future transformations with sustainability as kernel. These concepts could be imported in healthcare logistics and transport area for solving specific problems of this domain. Icam (French Engineer school) and FEI University are collaborating for proposing to healthcare hospitals a new framework (healthcare logistics 4.0) for solving complex problems of this domain. This paper is focusing on how to improve medicines procurement and dispatching in a hospital. Indeed, the use of Artificial Intelligence in healthcare sector is growing up. Data treated and analyzed could give important insights for solving problems and improving the existing organization. As machine learning is already exploited in many production management problems (forecasting, storage, production, etc.), the idea is to use it for developing an aided tool in addition to a lean manufacturing classical approach. After presenting the real problem of medicines procurement and dispatching detected in healthcare hospitals, concepts of lean manufacturing and machine learning will be exposed. Then, the methodology proposed for solving the problem will be shown. An illustration will be given for validating concepts presented. Finally, the link with the global “Healthcare logistics 4.0” framework will be described.
dc.description.firstpage1034
dc.description.lastpage1041
dc.description.volume38
dc.identifier.citationJORDON, K.; DOSSOU, PAUL-ERIC; CHANG JUNIOR, J. Using lean manufacturing and machine learning for improving medicines procurement and dispatching in a hospital. Procedia Manufacturing, v. 38, p. 1034-1041, 2019.
dc.identifier.doi10.1016/j.promfg.2020.01.189
dc.identifier.issn2351-9789
dc.identifier.urihttps://repositorio.fei.edu.br/handle/FEI/3426
dc.relation.ispartofPROCEDIA MANUFACTURING
dc.rightsAcesso Aberto
dc.rights.licenseCreative Commons "Este é um artigo publicado em acesso aberto sob uma licença Creative Commons (CC BY-NC-ND). Fonte: https://www.sciencedirect.com/science/article/pii/S2351978920301906?via%3Dihub. Acesso em: 03 out. 2021.
dc.subjectartificial Intelligence
dc.subjectmachine learning
dc.subjecthealthcare optimization
dc.subjectean manufacturing
dc.subjectDMAIC
dc.titleUsing lean manufacturing and machine learning for improving medicines procurement and dispatching in a hospitalpt_BR
dc.typeArtigopt_BR
fei.scopus.citations31
fei.scopus.eid2-s2.0-85083532330
fei.scopus.updated2024-11-01
fei.source.urlhttps://www.sciencedirect.com/science/article/pii/S2351978920301906?via%3Dihub
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