The friction coefficient in the simulation of stamping processes should be defined. Modern simulation software allows its definition as constant or its dependence on pressure or temperature. It is also useful in stamping processes to define different values in different regions, as it often reflects the nature of deformation process. This article deals with the regression and analytical models commonly used to determine the friction coefficients in specified areas of the stamping process. Analytical models were verified by an experimental strip drawing test under the same contact conditions. Steel sheets for the automotive industry were used in experiments and simulations—extra deep drawing quality DC 05 and austenitic stainless steel AISI 304. Friction coefficients were also evaluated when the cup test was performed. A regression model of drawing to the blankholding force was applied to the results. Conformity of friction coefficients when measured by cup tests and strip tests was confirmed. The values of the friction coefficient reached from the experiment were applied in FEM simulation software.
Digital technologies play a key role in reviving the world economy. The EU has pledged to combine recovery support with resilient digital transformation. The COVID-19 pandemic highlighted the lack of digitization in Slovakia and the shortcomings of digital skills in citizens and communication with institutions. Digital skills are important and should form part of educational policy. ICT skills can help people succeed in the labour market and improve communication with public administration. Digitization and globalization increase the importance to communicate through the Internet, applications, and other e-based gadgets. Digital skills are one of the essential parts of e-Government, so people can use e-Government services in communication with public administration. The current crisis is affecting citizens’ use of online services. Indices concerning the digital economy are analysed, such as the digital economy and society index DESI and e-Government digital skills (EGDI) from 2018 to 2021 revealed a stagnant state in 2018 and 2019, and in 2020, there was a decrease in basic digital skills. The next index is E-Government Digital Index. It focuses on human capital and digital skills in these indices. The paper analyses and identifies the digital skills of citizens in the context of e-Government development and describes the use of e-Government services by EU citizens with a focus on the Slovak Republic. The data were collected through a questionnaire survey of Slovak Republic citizens’ digital skills according to selected categories, the use of e-Government services as well as awareness of e-Government services. Solutions that improve e-Government in the Slovak Republic are gradually being implemented. Improving digital skills according to the National Coalition for Digital Skills and Professions in the Slovak Republic is one of the priorities of The Ministry of Education, Science, Research and Sport of the Slovak Republic, which has adopted an action plan for 2019–2022 to improve the results in the DESI index by 2025 and focus on the digital skills required by employers. The survey revealed that in Slovakia, the majority of schools offer only weak support for digital education (about the EU-27 average of 68% and 45%, respectively). The research also revealed a decreased level of digital literacy among young people. These competencies are very important to gain a position in the labour market in the digital society. The projects aim to support the development of digital skills of primary and secondary school students, and the integration of new technologies into teaching.
The main goal of this paper is to analyse the current system of maintenance in selected company and after identification of crucial problems, to propose the new system of maintenance that will be built based on predictive maintenance. The paper is divided into three sections. First section treats predictive maintenance in theoretical plane. Second section deals with analysis of current situation in the selected company in the maintenance area, while in this section you can find information about spare parts consumption and failure rate per year. Third section is about the proposal of improving maintenance status by introducing predictive maintenance.
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