Overview
Estimated Learning Time: 15 min
Description
19 single and multiple choice questions to evaluate the gained knowledge from the course ‘Cyber-Physical Production Systems’.
Topics and Learning Outcomes
- Systematize the obtained knowledge about what are Cyber-Physical Production Systems, main applications and relationship with other terms such as Industrial Internet of Things, Digital Twin, Sensorization, IEC 61499 and DINASORE.
- Verify the completion of the course ‘Cyber-Physical Production Systems’.
About The Author
Rui Pinto was born in Santa Maria de Lamas, Santa Maria da Feira, Portugal, on March 19, 1989. In 2013, he received a Master’s degree in Electrical and Computer Engineering from the Faculty of Engineering of the University of Porto (FEUP), and in 2022 a PhD in Computer Engineering from the same school. He is currently an Assistant Researcher at FEUP and an Integrated Member of the Research Center for Systems & Technologies (SYSTEC). He is also an Invited Teaching Assistant Professor at University of Trás-os-Montes and Alto Douro (UTAD). As an Invited Teaching Assistant Professor, he currently teaches course units in the Post-Graduation in Industrial Engineering and Management and Bachelor in Industrial Engineering and Management at UTAD, such as Intelligent Data Analysis, Industrial Systems in the Digital Age, and Seminar in Industrial Management and Engineering. Also, from 2017 to 2021, he taught at FEUP course units in the M.Sc. degree in Electrical and Computer Engineering (MIEEC), such as Programming Laboratories (LPRO) and Information Systems (SINF), and in the M.Sc. degree in Informatics and Computing Engineering (MIEIC), such as Project Management Laboratory (LGP). Since 2013, as a researcher, he has participated in at least 19 national and European Research and Development projects, mainly focused on the topics of digitization of industrial processes, WSAN, Edge/Cloud Computing, Smart Components, bio-inspired cybersecurity and Education 4.0. In addition, he had the opportunity to supervise and co-supervise at least 22 bachelor projects, Master’s dissertations and PhD thesis, on topics related to the smart industry paradigm.