On the use of simulation as a Big Data semantic validator for supply chain management

Vieira, Antônio; Dias, Luís M. S.; Santos, Maribel Yasmina; Pereira, Guilherme; Oliveira, José A.

doi:10.1016/j.simpat.2019.101985

Cited by 17 publications

(6 citation statements)

References 41 publications

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“…The simulation also served as a semantic validator of Big Data, due to the fact that the Big Data technology showed indetermination when analyzing the data that could be solved through simulation. This shows that Big Data technology requires improvement [ 51 ]. However, it is the analysis of Big Data that drives artificial intelligence to achieve sustainable manufacturing and circular economy capabilities [ 52 ].…”

Section: Resultsmentioning

confidence: 99%

Sustainability in the Aerospace, Naval, and Automotive Supply Chain 4.0: Descriptive Review

et al. 2020

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The search for sustainability in the Supply Chain (SC) is one of the tasks that most concerns business leaders in all manufacturing sectors because of the importance that the Supply Chain has as a transversal tool and due to the leading role that it has been playing lately. Of all the manufacturing sectors, this study focuses on the aerospace, shipbuilding, and automotive sectors identified as transport. The present study carries out a descriptive review of existing publications in these three sectors in relation to the sustainability of the Supply Chain in its 4.0 adaptation as an update in matters that are in constant evolution. Among the results obtained, Lean practices are common to the three sectors, as well as different technologies focused on sustainability. Furthermore, the results show that the automotive sector is the one that makes the greatest contribution in this sense through collaborative programs that can be very useful to the other two sectors, thus benefiting from the consequent applicable advantages. Meanwhile, the Aerospace and Shipbuilding sectors do not seem to be working on promoting a sustainable culture in the management of the Supply Chain or on including training programs for their personnel in matters related to Industry 4.0.

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Section: Resultsmentioning

confidence: 99%

Sustainability in the Aerospace, Naval, and Automotive Supply Chain 4.0: Descriptive Review

et al. 2020

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“…It is a time-consuming task that involves everything from data acquision until visualization and presentation. As data scales reach petabyte levels, traditional data processing tools produce unsatisfactory results when working with such complex structure and volumes of datasets [22]. Traditional data analytics methods face many challenges when dealing with big data such as coding/decoding, processing, pattern detection and analysis, transfer and sharing, as well as scale and complexity issues when analyzing such large amounts of data, due to its unstructured and heterogeneous nature [1], We can create better computational models that lead to better decision-making, which can be applied to a wide range of real-world scenarios [15].…”

Section: Big Data Analytics In Iot-enabled Gscm 31 Big Data Analyticsmentioning

confidence: 99%

Statistical techniques for big data analytics in IoT-enabled green supply chain management: a survey

Saleha

Abdelkaderb

Rashada

et al. 2023

المجلة العربية للقياس والتقويم

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In the manufacturing operation, intelligent Supply Chain Management systems (SCMS) can improve the quality of products, reduce cost, and accelerate the decision making process. The incorporation of environmentally sustainable processes into SCMS minimizes the overall environmental impact which is the target of Green Supply Chain Management (GSCM). The intelligence of the GSCM systems makes the business smarter. For this reason, it is always a concern to utilize cutting-edge ideas and technologies to optimize the operation of these systems. Internet of Things (IoT) is a promising Information technological (IT) concept that allows environmental objects to communicate with each other automatically and without human intervention. IoT is one of the most important IT solutions that provides intelligence and sustainability to GSCM systems. The significant feature of IoT is the huge volumes of data, called "big data" generated by the IoT sensors, installed on the different entities of the chain. To this end, big data processing in real time is a need for decision makers to preserve their companies" competitive advantage. There are many big data analytics techniques in the literature to target this issue. Our work will focus on surveying the statistical techniques that can be used in the analysis of big data generated from the IoT sensors situated on the different parts of GSCM to

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“…La Industria 4.0 busca aplicar factores de eficiencia, eficacia y exactitud para la toma de decisiones organizacionales (Vieira et al, 2020). La evolución tecnológica y su aplicación a los sistemas de producción y manufactura genera nuevos escenarios de desarrollo industrial (Araque et al, 2021).…”

Section: Nuevas Tecnologías: ¿De Qué Se Trata?unclassified

Nuevas tecnologías y organizaciones del sector público en Perú

Curo¹,

López²,

Li³

et al. 2022

RVG

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Las nuevas tecnologías de la llamada cuarta revolución industrial introducen profundos cambios en todas las áreas de la sociedad. En la gestión pública, estas herramientas representan grandes oportunidades para mejorar la atención al ciudadano y la prestación de servicios. Sin embargo, las dificultades de la sociedad latinoamericana y peruana representan grandes obstáculos para la aplicación de estos nuevos procesos a lo interno de las organizaciones del sector público. El objetivo de este trabajo precisar el uso de las nuevas tecnologías en organizaciones del sector público peruano. La investigación corresponde a un estudio descriptivo y de campo para lo cual se aplicó un cuestionario a los gerentes y usuarios de organizaciones públicas de Perú. Los resultados arrojaron que gran parte de los gerentes desconoce la importancia de estas nuevas tecnologías y, por otro lado, gran parte de la población desconoce de qué se tratan estas nuevas herramientas. En el ámbito organizacional, los principales usos que estas herramientas poseen están vinculados con la toma de decisiones, el procesamiento de datos y la multiposesión de información. Perú se encuentra en la fase inicial de aplicación de estas tecnologías.

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On the use of simulation as a Big Data semantic validator for supply chain management

Cited by 17 publications

References 41 publications

Sustainability in the Aerospace, Naval, and Automotive Supply Chain 4.0: Descriptive Review

Sustainability in the Aerospace, Naval, and Automotive Supply Chain 4.0: Descriptive Review

Statistical techniques for big data analytics in IoT-enabled green supply chain management: a survey

Nuevas tecnologías y organizaciones del sector público en Perú

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