CODE 111095 ACADEMIC YEAR 2024/2025 CREDITS 6 cfu anno 1 COMPUTER ENGINEERING 11160 (LM-32) - GENOVA SCIENTIFIC DISCIPLINARY SECTOR ING-INF/04 LANGUAGE English TEACHING LOCATION GENOVA SEMESTER 2° Semester TEACHING MATERIALS AULAWEB OVERVIEW This course provides essential modeling and methodological tools for addressing decision-making and management challenges in industrial systems. Focusing on the ANSI/ISA-95 international standard, students will learn to formalize and solve planning, scheduling, and control problems. Emphasis will be placed on the functions of Manufacturing Execution Systems (MES). By the end of the course, students will be proficient in positioning industrial automation issues within the ANSI/ISA-95 framework and resolving decision-making problems using appropriate methods and tools. AIMS AND CONTENT LEARNING OUTCOMES The course aims at providing the modeling and methodological tools for the formalization and resolution of some important decision-making and management problems in the context of industrial systems. During the course, planning, scheduling and control problems will be formalized and solved according to the framework proposed by the ANSI/ISA-95 international standard. Special focus will be devoted to the primary and support functions given by the Manufacturing Execution System (MES). At the end of the course, the student will be able to position an industrial automation problem in the context of ANSI/ISA-95 and to formalize and to solve decision-making problems, using proper methods and tools. AIMS AND LEARNING OUTCOMES By the end of the course, students will be able to: Position industrial automation problems within the context of the ANSI/ISA-95 framework. Formalize and solve decision-making problems using appropriate methods and tools. Design and implement automation solutions to optimize manufacturing processes. Identify MES functions to enhance production efficiency and quality control. Implement and tune PID controllers for various industrial applications. Program and deploy PLCs for automation tasks. Solve scheduling problems to optimize production timelines. Manage inventory effectively to balance supply and demand. Optimize delivery management to ensure timely and cost-effective distribution. Additionally, students will have developed: Advanced technical literacy skills Enhanced personal development skills Advanced interpersonal skills Proficiency in advanced project development Competence in foundational project management skills PREREQUISITES To ensure a successful learning experience in this course, students should have: Basic knowledge of constrained optimization problems, including their formalization. Understanding of database management and relational databases. TEACHING METHODS Approximately 30 hours are allocated for traditional lectures to cover the syllabus content comprehensively. The remaining hours are dedicated to hands-on activities, where practical exercises are conducted to reinforce theoretical concepts. These exercises progressively increase in complexity and are conducted within the MATLAB/Simulink environment, utilizing the MATLAB Control Toolbox extensively. During the lab sessions, students work on exercises under the guidance of the professor, leveraging MATLAB and Simulink to implement and analyze control systems. Continuous assessment is conducted based on the exercises completed during the lab sessions, ensuring ongoing engagement and learning reinforcement. Attendance of both lectures and lab sessions is mandatory to facilitate optimal learning outcomes. Furthermore, the course requires the development of a three-folded project, at the end of which the students submit a related report. This project allows students to apply their skills in advanced functional literacy, personal development, social interaction, project creation, and basic project management. Students with work commitments or certified special educational needs are encouraged to communicate with the instructor at the outset of the course. This ensures that teaching and examination arrangements are tailored to accommodate individual learning patterns while aligning with the course objectives. Students with certification of Specific Learning Disabilities (SLD), disabilities, or other special educational needs must contact the instructor at the beginning of the course to agree on teaching and examination methods that, while respecting the course objectives, take into account individual learning styles and provide appropriate compensatory tools. It is reminded that the request for compensatory/dispensatory measures for exams must be sent to the course instructor, the School representative, and the “Settore servizi per l'inclusione degli studenti con disabilità e con DSA” office (dsa@unige.it) at least 10 working days before the test, as per the guidelines available at the link: https://unige.it/disabilita-dsa SYLLABUS/CONTENT PART I: Introduction and Direct Control Introduction: Architectural Models in Industrial Automation Manufacturing Methods: Batch, Job, Flow Production Improvement Methods (Lean Manufacturing, Reliability-centered Maintenance, Zero Defects) Information and Communication Standards (ISA-88, ISA-95, ERP, IEC 62264, B2MML) Direct Control and Shopfloor: Shopfloor Description and Examples PID Control Exercises: Discrete Time Systems Simulation, Feedback Control Introduction Exercise: PID Control in Matlab and Simulink Ladder Logic Diagrams Generation in PLC programming PART II: Manufacturing Execution Systems Manufacturing Execution Systems: Definition and Models Who’s Who in MES MES Primary Functions Scheduling Methods and Tools Flow Shop Scheduling and Dynamic Programming for Scheduling Process Control and Quality Control MES Support Functions and Technologies PART III: MRP, MRPII and ERP Systems MRP, MRPII and ERP Systems: Definition and Models (Make to Order, Make to Stock) Basic Planning Level Problems Introduction Inventory Control and Demand Prediction Examples Inventory Routing Problems and Vehicle Routing Problem RECOMMENDED READING/BIBLIOGRAPHY S. French, Sequencing and Scheduling: An Introduction to the Mathematics of the Job-shop, 1982 M. McClellan, Applying manufacturing execution systems, 1997 TEACHERS AND EXAM BOARD ROBERTO SACILE Ricevimento: Contacts: Prof. Roberto Sacile, PhD c/o DIBRIS – University of Genova Polytechnic School via Opera Pia 13 16145 Genova, Italy Mob. +393281003228 Skype live:roberto.sacile_1 H323 130.251.5.4 http://orcid.org/0000-0003-4086-8747 Scopus Author ID: 56250207700 Exam Board ROBERTO SACILE (President) ENRICO ZERO MICHELE AICARDI (President Substitute) LESSONS LESSONS START https://corsi.unige.it/en/corsi/11160/students-timetable https://easyacademy.unige.it/portalestudenti//index.php?_lang=en Class schedule The timetable for this course is available here: Portale EasyAcademy EXAMS EXAM DESCRIPTION Project discussion and interview on the content of the course ASSESSMENT METHODS At the end of the course, the student must be able to simulate and control a simple system, design and implement the scheduling of jobs on machines, and to find optimal or sub-optimal strategies to manage the source, make, plan, and delivery process of an enterprise. Agenda 2030 - Sustainable Development Goals Industry, innovation and infrastructure