An Adaptive Algorithm and Additively Manufactured Punch Used to Form Aluminum Sheet Metal Parts.

Self-adaptive mechanisms are gaining momentum in industrial processes. It is understandable that as the complexity increases, the human work must be augmented. Considering this, the authors have developed one such solution for the punch-forming process, using additive manufacturing, i.e., a 3D-printed punch, to draw into shape 6061-T6 aluminum sheets. This paper aims to highlight the topological study used to optimize the punch form shape, the methodology of the 3D printing process, and the material used. For the adaptive algorithm, a complex Python-to-C++ bridge was created. It was necessary as the script has computer vision (used for calculating stroke and speed), punch force, and hydraulic pressure measurement capabilities. The algorithm uses the input data to control its subsequent actions. Two approaches are used in this experimental paper, a pre-programmed direction and an adaptive one, for comparison purposes. The results, namely the drawing radius and flange angle, were statistically analyzed using the ANOVA methodology for significance. The results indicate significant improvements when using the adaptive algorithm.

Erratum: Radu, M.-C., et al. The Impact of the COVID-19 Pandemic on the Quality of Educational Process: A Student Survey. Int. J. Environ. Res. Public Health 2020, 17, 7770.

In the original version of our article [...].

The Impact of the COVID-19 Pandemic on the Quality of Educational Process: A Student Survey.

The paper presents the results of a students' survey carried out at "Vasile Alecsandri" University of Bacau, Romania, on the quality of educational process on online platforms in the context of the COVID-19 pandemic. The study was addressed to students from the Faculty of Engineering and the Faculty of Physical Education and Sports. The results of survey highlighted that most of students were satisfied with the measures taken by the university during the lockdown period and the way the teaching-learning-assessment process took place. However, some negative aspects were reported as: lack of an adequate infrastructure for some students, less effective teacher-student communication and interaction, impossibility of performing practical applications, lack of socialization, lack of learning motivation, less objective examination (e.g., possibility of cheating), possibility of physical and mental health degradation (e.g., too much time spent in front of screens, installation of a sedentary lifestyle). Consequently, for the new academic year, effective, and efficient measures must be implemented by the management of the university to remove, as much as possible, these negative issues and to improve the performance of online educational process.