Abstract:

This work describes the design of the mini-course curriculum for mechanical engineering students to gain basic knowledge in the field of robotics, mechatronics, and Industry 4.0 as a part of the semester course. The course Mechatronics in Machine Design contains several mini-courses and is designed for students with limited preliminary knowledge of programming and electronics (mainly mechanical engineers). The focus is applied on the presenting of the basic concepts in the field of intelligent machine design. The whole curriculum of the mini course can be finished in 3 lecture blocks and should be able to provide sufficient knowledge to provoke the discussion between the students and the teacher that should result in preliminary design of the semestral group project (prototype of the mechatronic device). This approach could also make lessons more attractive for students because it shows the real-world applications of the lesson’s topic in a limited time, so students are not bored by spending so much time just listening about the topic. The main task is to pass on the necessary amount of information in the shortest possible time so the dialogue can be started, and further knowledge is gained by consultations with the supervisor or by students themselves. The main idea is not changing the environment but increasing the difficulty of the tasks. The used hardware for the lectures is the Raspberry Pi (or its alternatives) and industrial PLC (Programmable Logic Computer). The complexity of tasks can vary from elementary programming/ Linux lessons for beginners, sensor data reading and processing as the intermediate level, to advanced signal processing and machine learning for predictive maintenance. The introduction contains a review of problem-based learning methodology which is further applied in the field of engineering education. In the work several promising techniques describe the education of engineering subjects related to Industry 4.0. The first lesson includes using a Raspberry Pi for python programming, signal processing and hardware interaction for mechatronics essentials and predictive maintenance education. Basic programming concepts are presented during the simple programming course in python, supplemented by practical examples. Then a simple project is presented where the principles of sensor data reading, data processing and hardware control are shown, so the students can design the whole mechatronic system from input through data processing to actuator control. The second lesson is focused on image processing, so the students get familiar with the basic principles of machine vision, so they can incorporate camera sensors into their experiments. In the third lesson, the students learn about making digital twins in Siemens Tecnomatix Process Simulate. These vary from learning kinematics and robotics basics to planning and simulation of complex robotic / mechatronic systems. This tool, together with TIA (Totally Integrated Automation) Portal, allows them to design state of the art PLC applications that can transfer their knowledge from basic to the level of professional usage. The paper contains a description of beginner/intermediate stages of the education process that were already tested during the lessons during the academic year and the summer school and predicted a roadmap for further progression of planned advanced courses. In the final chapter of the paper, possible future work is described.

Keywords:

STEM Education, Raspberry Pi, Tecnomatix Process Simulate, TIA Portal, Engineering Education, Industry 4.0, IoT, Robotics, Scalable Education.