37065 - Automatic Machines T

Academic Year 2020/2021

  • Moduli: Andrea Zucchelli (Modulo 1) Andrea Zucchelli (Modulo 2)
  • Teaching Mode: Traditional lectures (Modulo 1) Traditional lectures (Modulo 2)
  • Campus: Bologna
  • Corso: First cycle degree programme (L) in Automation Engineering (cod. 9217)

Learning outcomes

Basic knowledge of automatic machines for discrete processes (functional concepts, architectures, operating methods, main criteria of their use).

Course contents

The course is organized into two modules, corresponding to 6 CFU and 3 CFU respectively. The two modules are developed synergistically during the lesson period.

1. The first module, with 6 CFU (60 hours), is organized in the following chapters:

M1-1 Historical Framework of Industrial Automation and Automatic Machines in the Bologna context

M1-2 Introduction to the fundamentals of Industrial Automation

M1-3 Basic parameters for calculating the productivity of an Automatic Machine

M1-4 Introduction to the calculation of Probabilities and Statistics with particular reference to the following topics:

- Definition of Probability

- Definition of Random Variable

- Models for Discrete Random Variables

- Models for Continuous Random Variables

- Methods for the Estimation of Parameters for Random Variables and Models for Random Variables

- Introduction to the Monte Carlo Method

- Probabilistic calculation of the productivity of an automatic machine and a line of Automatic Machines

M1-5 General overview of the main architectures of automatic machines:

- Complements about Machine Design, with particular regard to the following topics: (i) material fatigue, (ii) shafts and shaft components, (iii) screws for fixing and transmission of force and/or displacement, (iv) mechanical springs, (v) bearings and their assembly.

- Asynchronous Intermittent Machines

- Synchronous Intermittent Machines

- Continuous Machines

- Mixed Architecture Machines

M1-6 Introduction to the laws of motion commonly used in Automatic Machines

2. The second module of 3 CFU deals with systems that support the operation of an Automatic Machine. In particular, the systems treated are the following:

M2-1 systems for the deterministic or the probabilistic storage of product units

M2-2 systems for the extraction and transport of product units

M2-3 web-handling systems

Both modules are completed by exercises that are carried out by the teacher during the lessons. In addition, the teacher, during the lessons, assigns to the students some activities to be done at home and which must be collected in an exercise book that will be an integral part of the exam. Sometimes the teacher may also assign the completion of exercises that the teacher has set up during the lessons. The activities are assigned during the lessons, and there is no specific day on which the exercises are assigned and carried out.

Readings/Bibliography

1. Dispense del Corso

2. A. Zucchelli, Complementi per Macchine Automatiche, McGraw Hill Create, ISBN 9781307474541

3. Luigi Biagiotti · Claudio Melchiorri, Trajectory Planning for Automatic Machines and Robots, Springer-Verlag, 2008

4. Geoffrey Boothroyd, Peter Dewhurst, Winston A. Knight, Product Design for Manufacture and Assembly, CRC Press, Taylor & Francis Group, 2011

5. Geoffrey Boothroyd, Assembly Automation and Product Design, CRC Press, Taylor & Francis Group, 2005

6. Stephen J. Derby, Design of Automatic Machinery, Marcel Dekker, 2005

7. A.A.V.V., Advances in Future Manufacturing Engineering, CRC Press, Taylor & Francis Group, 2015

8. A.A.V.V., Future Mechatronics and Automation, CRC Press, Taylor & Francis Group, 2015

9. Bruno Lotter, Manufacturing Assembly Handbook, Butterworths, 1986

10. Marco Fortis, Monica Carminati, The Automatic Packaging Machinery Sector in Italy and Germany, Springer, 2015

Teaching methods

Frontal teaching in the classroom with use of slides and videos.

The course is developed both providing theoretical concepts and carrying out and assigning theoretical exercises and applications related to construction aspects of Automatic Machines.

To students are assigned exercises to be carried out autonomously and individually (only if specified by the teacher some exercises may be carried out in groups and, in this case, the names and surnames of the students who participated in the group must be specified in the homework book). These exercises must be collected, in an orderly manner, in a homework book that the students must bring to the exam for oral discussion.

Assessment methods

The learning verification of the topics covered during module 1 and module 2 will be carried out on the same day.

The verification will be carried out, preferably through an oral interview at a distance. During the oral test, the teacher will verify the knowledge of the theoretical topics and will check the application skills acquired in carrying out the exercises that have been assigned during the lessons and that the students will have collected in the dedicated homework book. In the case of a homework book written collaboratively, each member of the group who has collaborated in the writing of the exercise book will have to demonstrate a personal and total mastery of each exercise.

During the oral test, the teacher may also submit to the students transversal and reasoning questions regarding the topics and exercises covered in the lesson.

Variations on the exam method may be adopted by the teacher due to force majeure requirements and will be communicated to the students. Furthermore, should it be necessary due to a large number of students enrolled at the roll call, the teacher may submit to the students a multiple-choice test whose passing, with a minimum score of 18/30, will be necessary to access the oral exam. In this case, the questions of the oral examination will mainly focus on subjects not covered by the admission test.

Teaching tools

PowerPoint presentations and audiovisual

Office hours

See the website of Andrea Zucchelli

SDGs

Decent work and economic growth Industry, innovation and infrastructure

This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.