Industrial Information Systems

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This is a grouped course. It consists of several seperate subjects that share learning materials, assignments, tests etc. Below you can see information about the individual subjects that make up this subject.
Industrial Information Systems B3M33PIS
Credits 6
Semesters Winter
Completion Assessment + Examination
Language of teaching Czech
Extent of teaching 2P+2C
Annotation
The aim of this course is to provide students with the necessary set of skills essential for the design and management of modern production systems. In the first part of the course, the students will learn about methods of modeling and simulation of discrete production systems. Students will then gain insight into methods for data analysis to optimize the production as well as into methods for process mining. The final part of the course deals with methods of data and knowledge modeling, which are necessary for explicit capture and machine utilization of information and knowledge about production.
Study targets
The goal of the sourse is to introduce the information systems used in the industry, with principles of designing data models and with new trends comming form the industrial practice.

Course outlines
1. Models of discrete event systems
2. Petri nets
3. Analysis of Petri nets
4. Timed Petri Nets
5. Performance models
6. Software tools for modeling discrete production
7. Data analysis of production
8. Process mining
9. Introduction to semantics
10. Ontologies
11. OWL and SPARQL
12. Semantic reasoning
13. Description logic
14. Reserve

Exercises outlines
1. Plant Simulation
2. Assignment #1
3. Semantic Web Technologies
4. Assignment #2 - Semester project from SWT
5. System for ontology matching
6. Homework 1 - Semantics Assignment
7. Final Test










Literature
Cassandras, C.,G.; Lafortune, S. (2008): Introduction to Discrete Event Systems

F. Baader, The description logic handbook: theory, implementation, and applications, 2nd ed. Cambridge: Cambridge University Press, 2007

R. Brachman and H. J. Levesque, Knowledge Representation and Reasoning, Morgan Kaufmann, 2004

Requirements
Basic knowledge of relational DBMS, computer networking basics
Industrial Information Systems (Main course) BE3M33PIS
Credits 6
Semesters Winter
Completion Assessment + Examination
Language of teaching English
Extent of teaching 2P+2C
Annotation
The aim of this course is to provide students with the necessary set of skills essential for the design and management of modern production systems. In the first part of the course, the students will learn about methods of modeling and simulation of discrete production systems. Students will then gain insight into methods for data analysis to optimize the production as well as into methods for process mining. The final part of the course deals with methods of data and knowledge modeling, which are necessary for explicit capture and machine utilization of information and knowledge about production.
Study targets
The goal of the sourse is to introduce the information systems used in the industry, with principles of designing data models and with new trends comming form the industrial practice.

Course outlines
1. Models of discrete event systems
2. Petri nets
3. Analysis of Petri nets
4. Timed Petri Nets
5. Performance models
6. Software tools for modeling discrete production
7. Data analysis of production
8. Process mining
9. Introduction to semantics
10. Ontologies
11. OWL and SPARQL
12. Semantic reasoning
13. Description logic
14. Reserve

Exercises outlines
1. Plant Simulation
2. Assignment #1
3. Semantic Web Technologies
4. Assignment #2 - Semester project from SWT
5. System for ontology matching
6. Homework 1 - Semantics Assignment
7. Final Test

Literature
Cassandras, C.,G.; Lafortune, S. (2008): Introduction to Discrete Event Systems

F. Baader, The description logic handbook: theory, implementation, and applications, 2nd ed. Cambridge: Cambridge University Press, 2007

R. Brachman and H. J. Levesque, Knowledge Representation and Reasoning, Morgan Kaufmann, 2004




Requirements
Basic knowledge of relational DBMS, computer networking basics