La cuarta revolución industrial se presenta, en la actualidad, como un proceso de transformación y evolución productiva. El comportamiento globalizado de los mercados, las nuevas tendencias tecnológicas y el auge de innovadoras metodologías, han transformado la industria en un espacio de interacción interdisciplinar para la toma de decisiones organizacionales. Uno de estos espacios es la generación, obtención y análisis de los datos obtenidos de acuerdo con la relación hombre-máquina, también conocido en la actualidad como el Big Data. El presente artículo de investigación descriptiva tiene por objetivo exponer escenarios de aplicación, control y análisis de técnicas, tecnologías y metodologías asociados al Big Data en tres sectores principales: salud, financiero y transporte y logística. Los resultados obtenidos permiten evidenciar el impacto y relevancia con relación al mundo Big Data y sus aplicaciones en los sectores industriales de estudio como eje de reflexión y repercusiones profesionales. Se concluye que la integración de hardware y software en el campo del Big Data se hace indispensable en pro de la mejora de la calidad de servicio de teleasistencia en los pacientes, así como en los servicios logísticos y financieros
Purpose: Design an industrial production model with a focus on industry 4.0 (Big Data) and decision-making analysis for small and medium-sized enterprises (SMEs) in the clothing sector that allows improving procedures, jobs and related costs within the study organization Develop a sustainable manufacturing proposal for the industrial textile sector with a focus on Big data (entry, transformation, data loading and analysis) in organizational decision making, in search of time and cost optimization and environmental impact mitigation related.Design/methodology/approach: The present research, of an applied nature, raises a value proposition focused on the planning, design and structuring of an industrial model focused on Big Data, specifically in the apparel manufacturing sector for decision-making in a structured and automated way with the methodological approach to follow: 1) Approach of production strategies oriented in Big Data for the textile sector; 2) Definition of the production model and configuration of the operational system; 3) Data science and industrial analysis, 4) Production model approach (Power BI) and 5) model validation. Methodological design of the investigation. 1) Presentation of the case study, where the current situational analysis of the company is carried out, formulation of the problem and proposal of solution for the set of data analyzed; 2) Presentation of a solution proposal focused on Big Data, on the identification of the industrial ecosystem and integration with the company's information systems, as well as the solution approach in the study and science of data in real time; 3) Presentation of the Model proposal for SQL structured databases in the loading, transformation and loading of important information for this study; 4) Information processing, in the edition of data in the M language of Power BI software, construction and elaboration of the model; 5) Presentation of the related databases, in the integration with the foreign key of the Master table and the transactional Tables; 6) Data analysis and presentation of the Dashboard, in the design, construction and analysis of the related study variables, as well as the approach of solution scenarios in the correct organizational decision makingFindings: The results obtained show an improvement in operational efficiency from the value-added proposal. Research limitations/implications: Currently, the number of studies applying Big Data technology for organizations in the textile and manufacturing sector in organizational decision making are limited. If analyzed from the local scene, there are few cases of Big Data implementation in the textile sector, as a consequence of the lack of projects and financing of value propositions. Another limiting factor in this research is the absence of digital information of high relevance for study and analysis, which leads to longer times in data entry and placement in information systems in real time. Finally, there is no data organizational culture, where there are processes and/or procedures for data registration and its transformation into clean data.Originality/value: This research integrates, as well as the correct organizational decision making For the verification of originality, the project search and systematic review of literature in the main online search engines are carried out for this research; In addition, the percentages of coincidence with online reviewers such as turnitin and plag.es are reviewed in the transparency of this study project.
Planejamento, desenho e desenvolvimento metodológico de uma matriz de estruturação de custos ABC para o setor de saúde: estudo de caso Planning, design and methodological development of an ABC cost structuring matrix for the health sector: Case study
The industrial gasification operations sector has transformed the logistics of industrial processes in the production, distribution and supply of gas to customers, as a result of increased demand and market competitiveness. In the health sector, this type of behavior occurs on a daily basis, in order to meet the demand for medical gas (O2) supply in hospitals. The present investigation offers a proposal for methodological-investigative-mixed development, in relation to the study of times and methods focused on a gas supply company, in an effort to standardize processes. This is presented in five main phases: 1) Initial production diagnosis, with the analysis of the current productive behavior; 2) characterization and planning of the production proposal of the company being investigated; 3) purification and statistical treatment of information, analysis and sample intervention; 4) matrix construction and generation of production standards; 5) analysis of the results and presentation of the value proposition, through the application of engineering strategies and the cost-benefit ratio. The results obtained from the present investigation made it possible to optimize the operational times of the gas inspection process, filling of rack cylinders and mobile gas pumping by 14.72%, 6.46% and 8.02%, respectively.
Las lúdicas se ocupan del desarrollo de actividades que propician motivación en cualquier área de conocimiento en cuanto que permiten el aprendizaje significativo a través del juego. Los estudiantes necesitan resolver problemas, analizar la realidad y transformarla, deben estar en capacidad de enfrentarse a situaciones en las que requieran tomar decisiones para resolver escenarios que aquejan a las organizaciones en el día a día. Con esta edición de Propuesta pedagógica para el aprendizaje de herramientas de productividad a través de lúdicas, útil para docentes, estudiantes e investigadores, la REDPROD busca documentar un trabajo de campo que divulga el diseño, desarrollo y evaluación de los procesos de experimentación en función de doce nuevas estratégicas pedagógicas. Dentro de los resultados se encuentran aprendizajes relacionados con la calidad, los sistemas productivos, los métodos y tiempos, las cartas de control estadístico, la logística, la simulación, las finanzas y los BMP, entre otros conceptos propios de la ingeniería industrial y afines en términos de productividad.
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