Vol. 2 No. 1 (2023): Applications in Education and Sustainability Management in Industry 4.0 (January-June Issue)
The papers published in this issue bring together applications aimed at society, from the perspective of Education 4.0 and sustainable process management, integrating advanced Industry 4.0 technologies. The issue opens with the work of Fajardo-Pruna et al. (2023), who present a cyber-physical model of an IoT-based cutting machine, with the aim of optimizing manufacturing processes in the industry from a holistic perspective. Continuing with applications in the industry, Enríquez, F. et al. (2023) discuss the relevance of the architectural design pattern in the development processes of programs on the security, interoperability, and usability of computational systems. The aspects on which this analysis is based are essential to drive the digital transformation in industry and society. A very simple proof of this is the modular systems on which some applications are based that respond to the theory of business intelligence and educational applications. Suquisupa, A. et al. (2023) analyze the strategies implemented for waste management in industrial plants, from the perspective of collaborative management and the circular economy as a business model. Next, Andrade, G. et al. (2023) characterize milk production in indigenous populations of Ecuador, based on the study of marketing channels as an economic factor and the vulnerability of this sector of the population as a main social factor.
Other works complement this issue from a social perspective. Santana, C. et al. (2023) analyze the factors that cause traffic accidents by applying a deductive statistical analysis, to mitigate accidents in urban cities. Pule, V. et al. (2023) who determine the causes of tobacco use, as well as the perception of the consequences of consumption in student communities, and finally, Mejía, C. et al. (2023) analyze with a descriptive approach, the factors that influence the decision to study engineering careers by women. The analysis includes the perception of gender stereotypes as one of the main factors.
