design of mechatronic systems

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Applied Mechanics for Machinery
Second semester
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Learning outcomes of the course unit

Knowledge and understanding:
by means of frontal lessons, the student will acquire the methods and knowledge necessary to express or interpret the functional requirements of a mechatronic application for industrial automation, and to understand the design, implementation and validation criteria. The student will learn the structure and operating principle of automatic machines and the main subsystems that allow their automated operation. He will also learn some techniques for sizing drives for automation, functional design of mechanisms and parameterization of feedback controllers.
Applying knowledge and understanding:
through practical classroom exercises, students will learn how to carry out multiphysics simulations of automatic machine stations that integrate the different design aspects addressed in the course. In particular, the student will have to apply the acquired knowledge to the sizing and selection of drive systems from the catalog, to the kinematic design of mechanisms to satisfy assigned functional requirements and to the parameterization of a PID type feedback control, eventually with a cascade control approach.
Making judgements:
the student should be able to understand and critically evaluate the commercial solutions proposed for implementing specific industrial automation tasks in a production context. In particular, he has to be able to evaluate the adequacy of the approach followed and the technological choices adopted in relation to specific design requirements relating to movement control problems.
Communication skills:
through the front lessons and the assistance of the lecturer, the student acquires the specific vocabulary inherent in industrial automation, controllers, actuators and sensors. It is expected that at the end of the course the student will be able to transmit, in oral and written form, the main contents of the course, such as ideas, engineering issues and related solutions.
Learning skills:
the student who has attended the course will be able to deepen his knowledge of automation through the autonomous consultation of specialized texts, commercial catalogs and technical manuals, even outside the strictly lectured topics, in order to effectively address the insertion into the world of work or undertake further training paths.


There are no mandatory propaedeutics. Basic knowledge of Mechanics, Modeling of simple mechanical systems, Electrical circuits and components, and Programming fundamentals is required.

Course contents summary

The course offers a systemic and integrated vision of the functional design of automatic machines with particular reference to customized solutions for motion generation. The course deals with the issues of kinematic design of mechanisms and their driving by means of electric motors with axis control.
The exercises make use of multiphysics simulation software to learn the specific contents relating to the design of the kinematics, the sizing of the drives, the design of motion laws and the parameterization of the control loop.
These simulations also make it possible to test the interactions that link these different components of the system and to learn how to correctly plan the various design phases of a complex mechatronic system by applying the principles of simulation-driven-design.

Recommended readings

All the powerpoint presentations and the other content used during the lectures are available on Elly, as well as other useful resources. Among them, it worths mentioning video-recorded lectures, exercises and tutorials for remote learning.

In addition to the shared material, the student can personally study some of the topics discussed during the course in the following books:

Drive Solutions – Mechatronics for Production and Logistics, E.Kiel, Springer, e-ISBN 978-3-540-76705-3

Robotics – Designing the Mechanisms for Automated Machinery 2nd Edition, Ben-Zion Sandler, Academic Press, ISBN 0-12-618520-4

Principles of object-oriented modeling and simulation with modelica 3.3 – A cyber-physical approach 2nd Edition, P. Fritzson, IEEE Press Wiley, ISBN 9781118859124

Teaching methods

The course counts 6 CFUs (one CFU, University Credits equals one ECTS credit and represents the workload of a student during educational activities aimed at passing the exams), which corresponds to 48 hours of lectures. The didactic activities are composed of frontal lessons alternating with exercises. During the frontal lessons, the course topics are proposed from the theoretical and design point of view. During classroom exercises in labs students will apply theoretical knowledge to an exercise, a real case study, or a project.
The slides and notes used to support the lessons will be uploaded to the Elly Platform. To download the slides from Elly is required to enroll in the online course.
All the shared material is part of the didactic material. For non-attending students, it is important to stay up-to-date on the course through the Elly platform, the only communication tool used for direct teacher / student contact. On this platform, day by day, the topics discussed in the lesson are pointed out and registered, providing the students with an index of the contents for the final exam.

Assessment methods and criteria

Learning assessment takes place through an individual project plus the oral discussion of the same.
The project content is agreed with the lecturer at the beginning of the course and consists of a practical problem inherent in the main contents of the lessons. The project is completed with the delivery of the work done (e.g. source code of a program, CAD drawing of components, etc.) and a technical report of the work carried out.
The project must be delivered one week before the official date of the exam the student intends to take.
The project is evaluated as follows:
project development (max 10 points): understanding of the project requirements and objectives, prerequisite analysis, definition of functionality, performance and constraints; design; realization; integration, test and validation;
working method (max 10 points): independency, proactivity, creativity; research, analysis, evaluation and selection of different solutions; systematicity and essentiality; communication within the group and with the tutor;
results (max. 5 points): fulfillment of the original project's objectives;
Documentation (max 5 points): structure; completeness and correctness; style.
The final grade is equal to the sum of obtained points. The achieved points must be confirmed during the oral test which aims to verify the actual personal contribution of the student.
An exam is deemed to be passed successfully if the final grade is equal to or higher than 18/30. In the event of a full grade (30/30), the Examination Board may grant honours (lode) on the basis of the quality of the documentation and the oral presentation.