Model Proposal for Diagnosis and Integration of Industry 4.0 Concepts in Production Engineering Courses
Rodrigo Gris de Souza and
Osvaldo Luiz Gonçalves Quelhas
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Rodrigo Gris de Souza: Department of Production Engineering, Fluminense Federal University, Niterói 24210-240, Brazil
Osvaldo Luiz Gonçalves Quelhas: Department of Production Engineering, Fluminense Federal University, Niterói 24210-240, Brazil
Sustainability, 2020, vol. 12, issue 8, 1-15
Abstract:
In Industry 4.0, people need to be able to handle the vast amount of information from machines. In this sense, for Industry 4.0, higher education institutions play a fundamental role. The methodology of this article sought to identify the knowledge required by Industry 4.0 in the literature; carry out a diagnosis of the courses currently offered by Brazilian universities and the need to incorporate new knowledge, and validate the model in a real application. The survey is classified as exploratory, bibliographic and qualitative, supported by bibliometric research. As a result of the research, we identified that the technical content of courses needs to be reviewed to meet Industry 4.0 demand. Sixty-three per cent of respondents were production engineering course coordinators; 70% of respondents considered that the disciplines of current production engineering courses were not adequate to enable the production engineer to work in Industry 4.0. The priority knowledge for implementation in the curricula was identified as big data, advanced simulation, statistics for large amounts of information and virtual reality. It was also considered necessary to bring the industry closer to the universities. The model developed was applied and validated in a university that was evaluated with the highest score in the National Student Performance Exam (Enade).
Keywords: Industry 4.0; knowledge; production engineer (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:12:y:2020:i:8:p:3471-:d:349781
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