{"title":"Educational methods for Industry 4.0","authors":"Tomas Rericha, J. Navrátil, F. Steiner, J. Tupa","doi":"10.1109/Diagnostika55131.2022.9905099","DOIUrl":null,"url":null,"abstract":"Industry worldwide is facing new challenges, particularly the implementation of new technologies, climate change and currently the pandemic of the disease caused by the new coronavirus COVID-19. For the industry to be competitive, it must make technological changes. These changes are based on the concept of Industry 4.0. The changes brought about by implementing the Industry 4.0 concept and the related digitization of the economy have implications for the functioning of markets, industries, and other sectors. Significant impacts can be expected on the labor market when the demand for specific professions changes and new competencies will be required for employees. The fundamental question is how specifically these requirements can be implemented in current education conditions, specifically in the university environment. As part of practical training, it is unrealistic to demonstrate new ways of operation management on an extensive product line. It is very effective to use various forms of small-scale models. These models behave practically the same as in actual operation, and students can try out different production states, problem-solving and subsequent optimization. This article describes how we solve this problem in our university.","PeriodicalId":374245,"journal":{"name":"2022 International Conference on Diagnostics in Electrical Engineering (Diagnostika)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Diagnostics in Electrical Engineering (Diagnostika)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/Diagnostika55131.2022.9905099","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Industry worldwide is facing new challenges, particularly the implementation of new technologies, climate change and currently the pandemic of the disease caused by the new coronavirus COVID-19. For the industry to be competitive, it must make technological changes. These changes are based on the concept of Industry 4.0. The changes brought about by implementing the Industry 4.0 concept and the related digitization of the economy have implications for the functioning of markets, industries, and other sectors. Significant impacts can be expected on the labor market when the demand for specific professions changes and new competencies will be required for employees. The fundamental question is how specifically these requirements can be implemented in current education conditions, specifically in the university environment. As part of practical training, it is unrealistic to demonstrate new ways of operation management on an extensive product line. It is very effective to use various forms of small-scale models. These models behave practically the same as in actual operation, and students can try out different production states, problem-solving and subsequent optimization. This article describes how we solve this problem in our university.