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PORTALE DELLA DIDATTICA

Automation and planning of production systems

01PEDOV, 01PEDQW

A.A. 2019/20

Course Language

English

Course degree

Master of science-level of the Bologna process in Computer Engineering - Torino
Master of science-level of the Bologna process in Mechatronic Engineering - Torino

Course structure
Teaching Hours
Lezioni 48
Esercitazioni in laboratorio 12
Teachers
Teacher Status SSD h.Les h.Ex h.Lab h.Tut Years teaching
Rizzo Alessandro Professore Associato ING-INF/04 48 0 12 0 4
Teaching assistant
Espandi

Context
SSD CFU Activities Area context
ING-INF/04 6 B - Caratterizzanti Ingegneria informatica
2019/20
The course is entirely taught in English The students who complete this course will gain knowledge on fundamental concepts in modeling, control, and optimization of industrial production systems. Several components of actual production systems will be analyzed, and software tools for their modeling, control, and optimization, will be introduced. At the end of this course, students will gain knowledge on the role and working principles of the main components of modern production systems, as well as on the factors that determine their performance. Students will also be able to identify key issues in modeling and optimization of such systems, as well as to use software tools for modeling, simulation, and optimization. Each theoretical section will be complemented by laboratory experiences to elucidate practical issues and let students familiarize with software tools for modeling, control, and optimization of the systems under exam.
The course is entirely taught in English The students who complete this course will gain knowledge on fundamental concepts in modeling, control, and optimization of industrial production systems. Several components of actual production systems will be analyzed, and software tools for their modeling, control, and optimization, will be introduced. At the end of this course, students will gain knowledge on the role and working principles of the main components of modern production systems, as well as on the factors that determine their performance. Students will also be able to identify key issues in modeling and optimization of such systems, as well as to use software tools for modeling, simulation, and optimization. Each theoretical section will be complemented by laboratory experiences to elucidate practical issues and let students familiarize with software tools for modeling, control, and optimization of the systems under exam.
Students who complete this course will acquire the following knowledge: - Understanding the main components, structures and layouts of automated production plants, as well as of stocking areas and transportation systems. - Understanding the main metrics used to evaluate the performance of production systems, e.g., cycle time, production rate, availability, etc. - Understanding the issues connected to the selection of industrial robots components for applications, such as grippers or robotic cells. - Understanding the structure of most common CNC machines, with the use of CAD-CAM programming and their related G-code simulations. - Understanding the PLC architecture and the main programming techniques for automation applications. - Understanding statistical methods and numerical algorithms to assess the performance of queuing systems. - Understanding the main methods for the numerical solution of the most common production scheduling problems: single machine, parallel machines, flow shop, and job shop. - Understanding methods and algorithms for production planning: resource allocation, assignment, distribution. Students who complete this course will acquire the following abilities: - Acquiring the terminology related to modern production systems. - Assessing the performance indices of production systems, devising strategies identify factors that limit productivity and designing method for performance improvement and optimization. - Analyzing the performance of robot components for applications, such as grippers or robotic cells. - Interpreting and modifying machining codes for CNC machines, using simple CAD-CAM software tools to design workpiece machining. - Designing and implementing simple programs for PLCs, able to tackle real-world applications. - Modeling sections of production systems through queueing systems, assessing their performance, and identifying bottlenecks and margins for performance improvement. - Modeling scheduling problems for different production systems, and solving them, finding optimal or suboptimal solutions, through heuristic or linear programming approaches.
Students who complete this course will acquire the following knowledge: - Understanding the main components, structures and layouts of automated production plants, as well as of stocking areas and transportation systems. - Understanding the main metrics used to evaluate the performance of production systems, e.g., cycle time, production rate, availability, etc. - Understanding the issues connected to the selection of industrial robots components for applications, such as grippers or robotic cells. - Understanding the structure of most common CNC machines, with the use of CAD-CAM programming and their related G-code simulations. - Understanding the PLC architecture and the main programming techniques for automation applications. - Understanding statistical methods and numerical algorithms to assess the performance of queuing systems. - Understanding the main methods for the numerical solution of the most common production scheduling problems: single machine, parallel machines, flow shop, and job shop. - Understanding methods and algorithms for production planning: resource allocation, assignment, distribution. Students who complete this course will acquire the following abilities: - Acquiring the terminology related to modern production systems. - Assessing the performance indices of production systems, devising strategies identify factors that limit productivity and designing method for performance improvement and optimization. - Analyzing the performance of robot components for applications, such as grippers or robotic cells. - Interpreting and modifying machining codes for CNC machines, using simple CAD-CAM software tools to design workpiece machining. - Designing and implementing simple programs for PLCs, able to tackle real-world applications. - Modeling sections of production systems through queueing systems, assessing their performance, and identifying bottlenecks and margins for performance improvement. - Modeling scheduling problems for different production systems, and solving them, finding optimal or suboptimal solutions, through heuristic or linear programming approaches.
Basic to intermediate knowledge of MATLAB is required. Student lacking some background will be assisted in making it up through the suggestion of specific documentation, which has to be independently revised by the student.
Basic to intermediate knowledge of MATLAB is required. Student lacking some background will be assisted in making it up through the suggestion of specific documentation, which has to be independently revised by the student.
- Overview of manufacturing systems, manufacturing operations, manufacturing metrics and economics. - CNC Machines overview, introduction to programming with G-codes. Use of CAD-CAM based simulators for the generation of the G-codes. - Complementary topics in robotics for industry; e.g., selection of grippers, performance assessment of robotic cells, use of simulation tools to simulate robots (e.g., the Matlab Robotics Toolbox by Peter Corke). - Overview of material handling components. - Simulation of industrial production systems and their control in real time with PLCs. - Queuing theory applied to detect accumulation and bottleneck nodes of a production plant. Algorithms and statistical methods for reliability evaluation and quality control monitoring of production lots. - The main scheduling problems of automated production systems: single machine, parallel machines, flow shop and job shop. Solutions obtained by known rules when applicable or, in general, by numerical algorithms. - Methods and algorithms for production planning: resource allocation, assignment and distribution. - Conclusive remarks and exam simulation
- Overview of manufacturing systems, manufacturing operations, manufacturing metrics and economics. - CNC Machines overview, introduction to programming with G-codes. Use of CAD-CAM based simulators for the generation of the G-codes. - Complementary topics in robotics for industry; e.g., selection of grippers, performance assessment of robotic cells, use of simulation tools to simulate robots (e.g., the Matlab Robotics Toolbox by Peter Corke). - Overview of material handling components. - Simulation of industrial production systems and their control in real time with PLCs. - Queuing theory applied to detect accumulation and bottleneck nodes of a production plant. Algorithms and statistical methods for reliability evaluation and quality control monitoring of production lots. - The main scheduling problems of automated production systems: single machine, parallel machines, flow shop and job shop. Solutions obtained by known rules when applicable or, in general, by numerical algorithms. - Methods and algorithms for production planning: resource allocation, assignment and distribution. - Conclusive remarks and exam simulation
Theoretical foundations of each topic will be given in traditional in-class lectures. In-class lectures will be integrated by exercises, which will be partly solved in class and partly left to students for completion as homework. Each topic will be complemented by laboratory activities, aiming at describing one or more tools for the analysis and simulation of the systems under exams (e.g., simulators for robots, CNC machines, PLC, scheduling solvers, etc.)
Theoretical foundations of each topic will be given in traditional in-class lectures. In-class lectures will be integrated by exercises, which will be partly solved in class and partly left to students for completion as homework. Each topic will be complemented by laboratory activities, aiming at describing one or more tools for the analysis and simulation of the systems under exams (e.g., simulators for robots, CNC machines, PLC, scheduling solvers, etc.)
Handouts, notes, and program codes will be provided during the course. The instructor notes will include solved and unsolved exercises. Textbooks are not mandatory. Selected parts may be useful to understand more in-depth the concepts reported in handouts and notes. Texbooks 1. M.P. Groover, “Automation, Production Systems, and Computer-Integrated Manufacturing”, Pearson 2. H. Jack, “Automating Manufacturing Systems with PLCs”, free download at http://claymore.engineer.gvsu.edu/~jackh/books.html 3. P. Monkman et al., “Robot Grippers”, Wiley 4. C.G. Cassandras, S. Lafortune, “Indtroduction to Discrete Event Systems”, Springer 5. M.L. Pinedo, “Scheduling – Theory, Algorithms, and Systems”, Springer
Handouts, notes, and program codes will be provided during the course. The instructor notes will include solved and unsolved exercises. Textbooks are not mandatory. Selected parts may be useful to understand more in-depth the concepts reported in handouts and notes. Texbooks 1. M.P. Groover, “Automation, Production Systems, and Computer-Integrated Manufacturing”, Pearson 2. H. Jack, “Automating Manufacturing Systems with PLCs”, free download at http://claymore.engineer.gvsu.edu/~jackh/books.html 3. P. Monkman et al., “Robot Grippers”, Wiley 4. C.G. Cassandras, S. Lafortune, “Indtroduction to Discrete Event Systems”, Springer 5. M.L. Pinedo, “Scheduling – Theory, Algorithms, and Systems”, Springer
Modalità di esame: prova scritta;
Specific learning outcomes are assessed through the administration of a final written exam. Knowledge items will be assessed through the administration of theoretical exercises and problems concerning the description of the working principles of production systems. Abilities will be assessed through the administration of numerical exercises and problems, as well as through the design, analysis, or modification of software elements, written in the programming languages studied in class. The exam consists of a written test, aimed at assessing the comprehension of the theoretical concepts and the ability to apply them to practical case studies. The test consists of two sections: - the first section comprises 10 to 15 multiple-choice questions; - the second section comprises 3 to 5 problems. Such problems can be open-answer questions, numerical problems, coding problems. Incentives and penalties on the final marks may be given to students, in an amount not greater than the +/-10%, based on the active participation to the laboratory activities. Students abroad for study reasons and other particular cases will be evaluated on a case-by-case basis. The exam is closed-books, closed-notes. Students are allowed to take with them a single A4 sheet, which may be compiled on both sides with notes and formulae at their wish. The exam duration is 2 hours. An additional oral examination may only be requested by the instructor, in order to better assess the student’s preparation.
Exam: written test;
Specific learning outcomes are assessed through the administration of a final written exam. Knowledge items will be assessed through the administration of theoretical exercises and problems concerning the description of the working principles of production systems. Abilities will be assessed through the administration of numerical exercises and problems, as well as through the design, analysis, or modification of software elements, written in the programming languages studied in class. The exam consists of a written test, aimed at assessing the comprehension of the theoretical concepts and the ability to apply them to practical case studies. The test consists of two sections: - the first section comprises 10 to 15 multiple-choice questions; - the second section comprises 3 to 5 problems. Such problems can be open-answer questions, numerical problems, coding problems. Incentives and penalties on the final marks may be given to students, in an amount not greater than the +/-10%, based on the active participation to the laboratory activities. Students abroad for study reasons and other particular cases will be evaluated on a case-by-case basis. The exam is closed-books, closed-notes. Students are allowed to take with them a single A4 sheet, which may be compiled on both sides with notes and formulae at their wish. The exam duration is 2 hours. An additional oral examination may only be requested by the instructor, in order to better assess the student’s preparation.


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