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dc.contributor.authorKhan, Sohail Imran
dc.contributor.authorKaur, Chamandeep
dc.contributor.authorAl Ansari, Mohammed Saleh
dc.contributor.authorMuda, Iskandar
dc.contributor.authorCosio Borda, Ricardo Fernando
dc.contributor.authorBala, B. Kiran
dc.date.accessioned2023-10-24T17:24:54Z
dc.date.available2023-10-24T17:24:54Z
dc.date.issued2023-06-02
dc.identifier.citationKhan, S. I., Kaur, C., Al Ansari, M.S., Muda, I.,Cosio, R. F., & Bala, B. K. 82023). Implementation of cloud based IoT technology in manufacturing industry for smart control of manufacturing process. International Journal on Interactive Design and Manufacturing. https://doi.org/10.1007/s12008-023-01366-w
dc.identifier.other.es_PE
dc.identifier.urihttps://hdl.handle.net/11537/34739
dc.descriptionEl texto completo de este trabajo no está disponible en el Repositorio Institucional UPN por restricciones editoriales donde ha sido publicado.
dc.description.abstractInternet of Things (IoT) and Cloud Computing are receiving a lot of attention lately because they can offer a new technique for smart sensing and connectivity from man-to-man, man-to-machine, and machine-to-machine, as well as on-demand usage and effective sharing of resources, alternately. For the Industrial IoT to function as an infrastructure for data collection of shop floor equipment, cloud computing is required; distributed computing would move to the edge due to speed requirements for real-time processing of massive data. The method describes the standard manufacturing system built on a private cloud system that gathers data in real time from smart technologies linked to shop-floor objects.The study aims to design a general structure for information and data acquisition, processing, and collection at the edges of massive production controllers, where the approach is determined by the collection of shop-floor objects. The implementation of a multi-criteria adaptive scheduling technique that conducts accurate and effective scheduling or rescheduling of production processes in real time while taking shop-floor data and condition-based services into consideration. To move towards the Internet of Things, the different parts of the created cyber-physical mechanism will be applied in a cloud setting. The entities are made up of industrial assets that embed work-in-progress on items throughout their production phase of Cyber-Physical Production Systems (CPPS), which work together intelligently in such systems to achieve and maintain the manufacturing process's optimum, manage disruptions, and adapt to changing circumstances.The CPPS architecture joins a system with the IoT nodes made up of IoT accesses, and instruments, including PC-style terminals holding the resource agents with such a private cloud service. The decentralized MES network of a semi-hierarchical cloud-based CPPS controlling system is comprised of both networks. The development of the manufacturing process, controlling, monitoring, including optimization, as well as the archiving of historical data, are the major functions of the management system. The assessment of power consumed is presented together with an implementation framework. The entire method is easy to apply in different kinds of businesses and yielded incredibly satisfying results.es_PE
dc.formatapplication/pdfes_PE
dc.language.isospaes_PE
dc.publisherSpringer Parises_PE
dc.rightsinfo:eu-repo/semantics/closedAccesses_PE
dc.sourceUniversidad Privada del Nortees_PE
dc.sourceRepositorio Institucional - UPNes_PE
dc.subjectControllerses_PE
dc.subjectCyber Physical Systemes_PE
dc.subjectData acquisitiones_PE
dc.subjectData handlinges_PE
dc.subjectFloorses_PE
dc.subjectInformation managementes_PE
dc.subjectInternet of thingses_PE
dc.subjectProcess controles_PE
dc.titleImplementation of cloud based IoT technology in manufacturing industry for smart control of manufacturing processes_PE
dc.typeinfo:eu-repo/semantics/articlees_PE
dc.publisher.countryPEes_PE
dc.identifier.journalInternational Journal on Interactive Design and Manufacturinges_PE
dc.description.peer-reviewArtículo científicoes_PE
dc.subject.ocdehttps://purl.org/pe-repo/ocde/ford#2.11.04es_PE
dc.description.sedeComases_PE
dc.identifier.doihttps://doi.org/10.1007/s12008-023-01366-w


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