Director of studies: Prof. dr hab. inŝ. M. Galicki Name of lecturer: Prof. dr hab. inŝ. M. Galicki

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1 T H E O R Y O F C O N T R O L A N D R E G U L A T I O N Course code: 06.1-WM-MiBM-S1-AiOPP-02_ WM-MiBM-N1-AiOPP-02_09 Type of course: Language of instruction: Compulsory Polish Director of studies: Prof. dr hab. inŝ. M. Galicki Name of lecturer: Prof. dr hab. inŝ. M. Galicki Form of instruction tea ching hour s per semest er tea ching hour s per we ek Semest er Form of receiving a credit for a course ECTS credi ts alloca ted Full-time studies Lecture 15 1 Class - - Laboratory 30 2 VI Seminar - - W orkshop - - Project - - Part-time studies 3 Lecture 9 1 Class - - Laboratory 18 2 VI Seminar - - W orkshop - - Project - - COURSE AIMS: The aim of the course is to familiarize students with control systems: control objects and their division, stability systems, the objects identification, the design and testing of control systems. Transfer of knowledge of tasks formulating and problem solving of the dynamic objects control with particular emphasis on the mechanical systems. PREREQUISITIES: The mathematical analysis and probability, the ability to use IT tools: Matlab / Scilab

2 COURSE CONTENTS: Lecture content. Control and regulation systems and their classification. The cntinuous linear systems (controllability and observability). The choice of the state variables for the system (control object). The fundamental dynamic elements (inertial and noninertial elements, integral, derivative, proportionate, oscillating and delay elements). Stability of the linear systems. Quality and sensitivity of control systems. The observers of linear systems. The discrete linear systems. Controllability, observability and stability of the discrete linear systems. Unsteady continuous and discrete linear systems, non-linear systems. Basic types of elements of non-linear systems. Observability controllability of nonlinear systems. Stochastic processes in control systems. Optimal control. Laboratory content: MATLAB / Scilab software for modeling, simulation and analysis of dynamic systems. Determination of the time and frequency characteristics of the basic objects of regulation. Investigation of the operational control systems. Examination of the static and astatic control systems. Linear regulators - analysis of temporal characteristics. PID tuning. Characteristics and analysis of the selected objects and control systems. The study of stability control systems. Determination of the characteristics of nonlinear static elements. Analysis of selected non-linear systems. TEACHING METHODS: Lectures with audiovisual aids. Working with the book and journals. Individual and group work in laboratory classes. Presentation of solutions, discussion of the obtained solutions. LEARNING OUTCOMES: The reference to the learning outcomes of the field of study K_W08 K_W08 K_U08 K_U18 K_U13 K_U08 K_U09 K_U15 K_U01 K_U05 Knowledge, skills, competence Is able to characterize the different control systems and to formulate a mathematical description of real control objects Can name the basic dynamic elements and make a mathematical description of these elements. He can analyze the action of selected control and regulation systems. He can design a control system and simulate its operation. Can use software tools for modeling, simulation and analysis of objects and control systems. Shall evaluate of control systems and properly selects the parameters of such systems. Is determined to find a task solutions LEARNING OUTCOMES VERIFICATION AND ASSESSMENT CRITERIA: The verification methods for learning outcomes are presented in the table below: The reference to the learning outcomes of the field of study K_W08 K_W08 K_U01 K_U05 K_U08 K_U09 K_U13 K_U15 K_U18 Written test The method of the learning outcomes assessment Assessment of the laboratory is based on: the laboratory exercises and reports/programs resulting from the execution of all exercises to be exercised. To get a credit the student has to receive all passing grades. The final grade received by the student is the arithmetic mean of the above grades.

3 STUDENT WORKLOAD: The student workload of 76 (73) hours, including work in the auditorium 45 (28) hours, consultations 1 (1) hours, and individual work 30 (45) hours, including: preparation for classes and preparation of reports and audit work 25 (30) hours, preparation for the written test 5 (15) hours. Total hours of practical classes: 56 (49) which corresponds to 2 ECTS. Total hours of lessons with a teacher: 46 (28) which corresponds to 2 ECTS RECOMMENDED READING: 1. T. Kaczorek, Teoria sterowania i systemów, WNT, Warszawa, 1999, 2. T. Kaczorek i inni, Podstawy teorii sterowania, WNT, Warszawa Jędrzykiewicz Z.: Teoria sterowania układów jednowymiarowych. Wydawnictwa AGH. Kraków H. Górecki, Algorytmy i programy sterowania, WNT, Warszawa, 1980, 5. Z. Budnicki, Teoria i algorytmy sterowania, Wydawnictwo Naukowe PWN, Warszawa, 2002, 6. Włodzimierz Kwiatkowski, Podstawy teorii sterowania. Wybrane zagadnienia. BEL K. Ogata, Metody przestrzeni stanów w teorii sterowania, WNT, Warszawa 1974r. 8. Chorowski B., Werszko M., Mechaniczne Urządzenia Automatyki, Wydawnictwo Naukowo-Techniczne, Warszawa 1975 i nowsze, OPTIONAL READING: 1. Amborski K., Marusak A., "Teoria sterowania w ćwiczeniach". PWN, Warszaw REMARKS: Workloads in parentheses are the numbers for part time studies.

4 L O G I S T I C S Course code: Type of course: Language of instruction: Director of studies: Name of lecturer: 06.1-WM-MiBM-S1-AiOPP-06.1_ WM-MiBM-N1-AiOPP-06.1_09 Optional Polish dr inŝ. Edward Tertel dr inŝ. Edward Tertel dr inŝ. Joanna Cyganiuk dr inŝ. Piotr Kuryło Form of instruction tea ching hour s per semest er tea ching hour s per we ek Semest er Form of receiving a credit for a course ECTS credi ts alloca ted Full-time studies Lecture 15 1 Exam Class - - Laboratory 30 2 VII Seminar - - W orkshop - - Project - - Part-time studies 5 Lecture 9 1 Exam Class - - Laboratory 18 2 VII Seminar - - W orkshop - - Project - - COURSE AIMS: The aim of the course is to introduce students to the basic issues of materials and decisions flow at all stages of the production (sourcing, manufacturing, distribution). Knowledge of logistics infrastructure, and principles of selecting and design of its elements. To get acquainted with modern methods of logistics management. Awareness of importance of logistics of both economic as well as social terms. PREREQUISITIES:

5 Mathematics Technological processes, Automation and Robotics. COURSE CONTENTS: Lecture content. The essence of logistics, definitions, origin, the essence of logistics management, the system approach and the process approach in logistics. Supply chain management. Logistics as a system - goals - elements - processes - environment. Classification of logistics tasks. Classification of logistics systems (institutional, material and functional criterions). The strategic importance of logistics. The transport as a subsystem of logistics (the transport infrastructure). Packaging in logistic systems. Storage, Warehouse infrastructure. Logistic centers. The logistic tasks in various business stages: supply, production, distribution and utilization. Laboratory content: Identification of the basic operational, quality and logistics indicators in robotic manipulation of unit loads. Control of the flow process of liquid and semi-liquid media - the use of the sensors in the dispensing of media distribution systems. Identification of the unit loads in distribution systems using the barcode technology. Control of the goods flow process of - the use of the bar code scanners in the process of distribution of cargo. Determining of the Cartesian pneumatic manipulator workspace in the implementation of handling functions. Determination of the basic parameters of the selected handling equipment. Load manipulation in the automated picking process of loading units - functions and parameters. Determination of the functional parameters of cargo storage equipment warehouses. TEACHING METHODS: Lectures with audiovisual aids. Working with the book and journals. Individual and group work in laboratory classes. Presentation of solutions, discussion of the obtained solutions. LEARNING OUTCOMES: The reference to the learning outcomes of the field of study K_W18, K_W18 K_U18 K_W18 K_U18 K_U18 K_U10 K_K02 K_K01 Knowledge, skills, competence Is able to define basic concepts of logistics and classify and describe main tasks/goals of the logistic system. Distinguishes between the methods of storage products in warehouses and their corresponding infrastructure. Is able to plan distribution products in the warehouse using basic methods of inventory management. He can to name and give a short description the logistics infrastructure elements. He can select / design the logistics infrastructure elements for a specific task, in particular, of storing and handling. Can design packaging and form of the unit load for a given product, and use the appropriate method of storage Is conscious of the importance of logistics in the economy. Sees rapid development of logistic infrastructure and is aware of the need to tracking changes in this area. LEARNING OUTCOMES VERIFICATION AND ASSESSMENT CRITERIA: The verification methods for learning outcomes are presented in the table below: The reference to the learning outcomes of the field of study K_W18, K_U10 K_U18 Exam, audit work The method of the learning outcomes assessment Assessment of of the course is determined on the basis of ratings for audit work (weight = 0.4) and exam (weight = 0.6). Assessment of the laboratory is based on: the laboratory exercises and reports/programs resulting from the execution of all exercises to be exercised.

6 K_K01 K_K02 To get a credit the student has to receive all passing grades. The final grade received by the student is the arithmetic mean of the above grades. STUDENT WORKLOAD: The student workload of 125 (125) hours, including work in the auditorium 45 (27) hours, consultations 3 (1) hours, participations in the exam 2 (2) hours, and individual work 75 (95) hours, including: preparation for classes and preparation of reports and audit work 50 (70) hours, preparation for the exam 20 (25) hours. Total hours of practical classes: 88 (87) which corresponds to 3 ECTS. Total hours of lessons with a teacher: 45 (27) which corresponds to 2 ECTS RECOMMENDED READING: 1. Blaik P., Logistyka, PWE, Warszawa, Stanisław KrzyŜaniak, Piotr Cyplik Zapasy i magazynowanie, ILiM Marek Fertsch, Piotr Cypli, Logistyka produkcji. Teoria i praktyka ILiM Coyle J., Bardi E., Langley J., Zarządzanie logistyczne, PWE, Sarjusz-Wolski Z., Skowronek C., Logistyka, CIM, Warszawa Korzeń Zb., Logistyka w transporcie towarów, Korzeń Zb., Logist. syst. transp. bliskiego i magaz OPTIONAL READING: 1. Logistyka dwumiesięcznik. 2. Logistyka a jakość dwumiesięcznik 3. Nowoczesny magazyn - dwumiesięcznik REMARKS: Workloads in parentheses are the numbers for part time studies.

7 A N A U T O M A T E D T R A N S P O R A N D S T O R A G E Course code: 06.1-WM-MiBM-S1-AiOPP-06.2_ WM-MiBM-N1-AiOPP-06.2_09 Type of course: Language of instruction: Optional Polish Director of studies: dr inŝ. Edward Tertel dr inŝ. Edward Tertel Name of lecturer: dr inŝ. Joanna Cyganiuk dr inŝ. Piotr Kuryło Form of instruction tea ching hour s per semest er tea ching hour s per we ek Semest er Form of receiving a credit for a course ECTS credi ts alloca ted Full-time studies Lecture 15 1 Exam Class - - Laboratory 30 2 VII Seminar - - W orkshop - - Project - - Part-time studies 5 Lecture 9 1 Exam Class - - Laboratory 18 2 VII Seminar - - W orkshop - - Project - - COURSE AIMS: Acquainting students with the problems in the field of materials handling and storage, with particular reference to the automation of these processes. Discussion of the problems of packaging and loading units as elements allowing automation. Acquainting students with equipment to enable automated handling and storage - the principles of selection of equipment as well as selected aspects of their operation. PREREQUISITIES:

8 Technological processes Automation and Robotics. COURSE CONTENTS: Lecture content. The essence of logistics, definitions, origin, the essence of logistics management, the system approach and the process approach in logistics. Characteristics and tasks of the transportation systems. The strategic importance of internal transport. Packaging. Loading units. The dimensional systems of packaging and loading units. Characteristics of machinery and equipment used in the technological transport - automated machines. The use of automated transport trucks in the storage transport. Interoperability in the transport processes. Warehouse Infrastructure, automated warehouse. Transport and storage process automation. Compatibility with automated high-storage warehouse. Laboratory content: Packaging design and selection of the dimensions of loading units. Identification of the basic operational, quality and logistics indicators in robotic manipulation of unit loads. Determining of the Cartesian pneumatic manipulator workspace in the implementation of handling functions. Determination of the basic parameters of the selected handling equipment. Load manipulation in the automated picking process of loading units - functions and parameters. Determination of the functional parameters of cargo storage equipment warehouses. TEACHING METHODS: Lectures with audiovisual aids. Working with the journals. Individual and group work in laboratory classes. Presentation of solutions, discussion of the obtained solutions. LEARNING OUTCOMES: The reference to the learning outcomes of the field of study K_W18, K_W18 K_W18 K_W18 K_U18 K_U18 K_U15 K_U18 K_U10 K_K02 K_K01 Knowledge, skills, competence Is able to define basic concepts of logistics He can classify and describe main tasks of the handling and storage systems. He can name and give a short description of infrastructure elements of handling and storage, with particular reference to automation. Is able to define notion of packaging, classify of packaging, explain the basic functions of packaging and characterize the packaging dimensional system. He can select/design the infrastructure elements for the specific logistics task in the field of automated storage and handling. Can design the collective packaging and form of the unit load for a given product and use the appropriate method of storage. He can analyze the possibility of automation in the processes of storage and handling Is conscious of the importance of logistics in the economy. Sees rapid development of logistic infrastructure, especially in terms of automated equipment and is aware of the need to tracking changes in this area. LEARNING OUTCOMES VERIFICATION AND ASSESSMENT CRITERIA: The verification methods for learning outcomes are presented in the table below: The reference to the learning outcomes of the field of study K_W18, K_U10 K_U15 Exam, audit work The method of the learning outcomes assessment Assessment of of the course is determined on the basis of ratings for audit work (weight = 0.4) and exam (weight = 0.6). Assessment of the laboratory is based on: the laboratory exercises and reports/programs resulting from the execution of all exercises to be exercised.

9 K_U18 K_K01 K_K02 To get a credit the student has to receive all passing grades. The final grade received by the student is the arithmetic mean of the above grades. STUDENT WORKLOAD: The student workload of 125 (125) hours, including work in the auditorium 45 (27) hours, consultations 3 (1) hours, participations in the exam 2 (2) and individual work 75 (95) hours, including: preparation for classes and preparation of reports and audit work 50 (70) hours, preparation for the exam 20 (25) hours. Total hours of practical classes: 88 (87) which corresponds to 3 ECTS. Total hours of lessons with a teacher: 45 (27) which corresponds to 2 ECTS RECOMMENDED READING: 1. Coyle J., Bardi E., Langley J., Zarządzanie logistyczne, PWE, Sarjusz-Wolski Z., Skowronek C., Logistyka, CIM, Warszawa Korzeń Zb., Logistyka w transporcie towarów, Korzeń Zb., Logist. syst. transp. bliskiego i magaz OPTIONAL READING: 1. Logistyka dwumiesięcznik. 2. Logistyka a jakość dwumiesięcznik 3. Nowoczesny magazyn - dwumiesięcznik REMARKS: Workloads in parentheses are the numbers for part time studies.

10 M O D E L L I N G A N D S I M U L A T I O N O F P R O C E S S E S Course code: 06.1-WM-MiBM-S1-AiOPP-06_ WM-MiBM-N1-AiOPP-06_12 Type of course: optional Language of instruction: English Director of studies: dr inŝ. Joanna Cyganiuk Name of lecturer: dr inŝ. Joanna Cyganiuk Form of instruction teaching hours per semester teaching hours per week Semester Form of receiving a credit for a course ECTS credi ts alloca ted Full-time studies Lecture 15 1 Exam Class Laboratory 30 2 VI Seminar W orkshop Project Part-time studies 5 Lecture 8 1 Exam Class Laboratory 18 2 VI Seminar W orkshop Project COURSE AIM: The aim of the course is to familiarize students with the methods of mathematical and physical modeling as well as with methods and techniques of processes simulation. To familiarize students with the options of the use of the methods in modeling and simulation of processes like: production, transport, manipulation and machines automation occurring in these processes. ENTRY REQUIREMENTS: Mathematics, Physics, Engineering Mechanics, Fundamentals of Machine Design, Automation and Robotics, The ability to use basic computer tools, Wydział Mechaniczny Kierunek: Mechanika i Budowa Maszyn

11 COURSE CONTENTS: The content of the lecture: Basic concepts connected with modelling and simulation of processes: model, system, simulation, process. Model construction. Types of models and algorithms of modelling processes. Issues connected with mathematical and physical modelling and simulation of processes: data types and their collection, define parameters and variables, define a problem. Methods of formalization of description of process and object. Apparatus of dimensional analysis - theorem π. Modelling with the use of dimensional functions. Queuing models. Network models. Petri network. Scheduling. Computer tools in modelling and simulation of processes. The use of practical examples of modeling and simulation methods. The content of the laboratory: Create virtual models, dimensional analysis and simulation of appliances used in automation of production and transport processes. The use of queueing models queueing systems with or without queue. The use of network models in analysis of automated production systems including Petri network. The use of operation planning schedules including automation and manufacturing processes. TEACHING METHODS: Lecturers are given with the use of multimedia technics. Work with specialist literature textbooks, professional journals. Laboratories are given with the use of computer software methods: problem tasks, solution analysis. Individual and group job during the realization of laboratory exercises. LEARNING OUTCOMES: In the field of technical sciences K_W12 K_W16 K_W22 K_U08 K_U09 K_U13 K_U15 K_K04 K_K06 Knowledge, skills, competence The student knows computational methods, basic tools and techniques of informatics needed in solving engineering tasks which are essential in modeling and processes simulation. The student has knowledge of the simulation and analysis of mechanical systems, automation, transport and manipulation appliances and production processes. The student can plan and carry out computer simulations, to interpret the results and to draw conclusions. The student uses modern simulation and analytical computational methods for modeling and simulation of processes like engineering problems. The student can make a critical analysis of the way of functioning of processes of modeling and simulation including used in processes appliances, operations, and planning methods. The student can identify aims and priorities used for tasks set by him and others. The student can demonstrate the ingenuity and skill in selection of appropriate modeling and simulation methods, depending on considered problem. Wydział Mechaniczny Kierunek: Mechanika i Budowa Maszyn

12 LEARNING OUTCOMES VERIFICATION AND ASSESSMENT CRITERIA: Rules for the verification of learning outcomes are presented in the table below. In the field of technical Knowledge, skills, competence sciences K_W12 K_W16 K_W22 K_U08 K_U09 K_U13 K_U15 K_K04 K_K06 The Exam. The Exam is based on written test. It is an arithmetic average from grades of written answers. The is based on realization of laboratory classes. The laboratory is determined from lab reports and from modeling results. The laboratory is an arithmetic average from grades of reports and from modelling results. To get a credit the student has to pass all course forms. The final grade received by the student is the arithmetic mean of the above grades. STUDENT WORKLOAD: The student workload of 127(113) hours, including work in the auditorium 45(27) hours, participate in consultations 15(20) hours, individual work 65(64) hours including preparation for classes and study reports, 35(39) hours, exam preparation 25(20) hours. Total hours of practical classes: 80(77) which corresponds to 3 ECTS Total hours of lessons with a teacher: 62(49), which corresponds to 2 ECTS RECOMMENDED READING: 1. Barker R., Longman C., Modelowanie funkcji i procesów, WNT, Warszawa 1996, 2. Kacprzyk J., Modelowanie i optymalizacja: metody i zastosowania, Akademicka Oficyna Wydawnicza EXIT, Warszawa 2002, 3. Iwanik A., Misiewicz J. K., Wykłady z procesów stochastycznych z zadaniami. Cz. 1, Procesy Markowa, Oficyna Wydawnicza Uniwersytetu Zielonogórskiego, Zielona Góra 2009, 4. Kasprzak W. Lysik B., Analiza wymiarowa: algorytmiczne procedury obsługi eksperymentu, WNT, Warszawa Krupa Krzysztof, Modelowanie symulacja i prognozowanie, WNT, Warszawa 2008, 6. Starke P. H., Sieci Petri: podstawy, zastosowania, teoria, PWN, Warszawa 1987, 7. Zdanowicz R., Modelowanie i symulacja procesów wytwarzania, Wydawnictwo Politechniki Śląskiej, Gliwice 2007, OPTIONAL READING: 1. Abramov S. A., Marinicev M. I., Polakov P. D., Metody analizy sieciowej w planowaniu i zarządzaniu, Wydawnictwo MON, Warszawa 1967, 2. Korzeń Z., Logistyczne systemy transportu bliskiego i magazynowania Tom II Projektowanie, modelowanie, zarządzanie, ILiM, Poznań 1998, 3. Modelowanie inŝynierskie czasopismo, 4. Oniszczuk W.: Metody modelowania, Wyd. Politechnika Białostocka, Białystok 1995, 5. Gnedenko B.V. Kovalenko I. N., Wstęp do teorii obsługi masowej, PWN, Warszawa1971. REMARKS: The student workloads written in brackets are the numbers for external studies. Wydział Mechaniczny Kierunek: Mechanika i Budowa Maszyn

13 S U P E R V I S I O N S Y S T E M S A N D V I S U A L I S A T I O N O F P R O D U C T I O N P R O C E S S E S Course code: 06.1-WM-MiBM-S1-AiOPP-07_ WM-MiBM-N1-AiOPP-07_12 Type of course: optional Language of instruction: English Director of studies: dr inŝ. Joanna Cyganiuk Name of lecturer: dr inŝ. Joanna Cyganiuk Form of instruction teaching hours per semester teaching hours per week Semester Form of receiving a credit for a course ECTS credi ts alloca ted Full-time studies Lecture 15 1 Exam Class Laboratory 30 2 VI Seminar W orkshop Project Part-time studies 5 Lecture 9 1 Exam Class Laboratory 18 2 VI Seminar W orkshop Project COURSE AIM: The aim of the course is to familiarize students with the supervision and visualization systems used in production processes. To familiarize students with the applied methods of supervision of production processes including appliances supporting their supervision as well as with the methods of computer visualization used in automated processes like production, transport, manipulation. ENTRY REQUIREMENTS: Mathematics, Physics, Engineering Mechanics, Fundamentals of Machine Design, Automation and Robotics, The ability to use basic computer tools, Wydział Mechaniczny Kierunek: Mechanika i Budowa Maszyn

14 COURSE CONTENTS: The content of the lecture: Process definition, division of supervision processes. Types of supervised physical, geometrical and electrical quantities and their division. Methods and means for processes supervision. The concept of processes visualization and areas of its application. Introduction to the SCADA systems. Discussion of methods for creating visualization applications on the example of the Wonderware In Touch. Presentation methods for creating visualization applications in In Touch program for sample processes. The content of the laboratory: Collecting information from external sensors working with the controller and with the sensors analyzing signals from processes. Creating applications in In Touch program for given process conditions and analysis of application correctness and its modernization. Cooperation between application and controller. TEACHING METHODS: Lecturers are given with the use of multimedia technics. Work with specialist literature textbooks, professional journals. Laboratories are given with the use of computer software methods: problem tasks, solution analysis. Individual and group job during the realization of laboratory exercises. LEARNING OUTCOMES: In the field of technical sciences K_W12 K_W16 K_W22 K_U08 K_U13 K_U15 K_U17 K_K04 K_K06 Knowledge, skills, competence The student knows supervision and visualization methods, used in production processes, transport processes, manipulation processes and processes of automation. The student has knowledge of the supervision systems and appliances used in these systems as well as he has knowledge in the processes visualization area which are characteristic for automated production. The student can create application which is used for simulation and visualization of production processes, he is able to collect process data and use them for visualization and for interpretation state of process. He is able to draw conclusions and suggest solutions. The student can use modern computational methods for creating the application for solving engineering problems in the range of supervision of manufacturing systems. The student can make a critical analysis of the way of functioning of supervising appliances and of the way of working created applications. The student can assess usefulness appliances used for supervision of manufacturing processes. He knows how to select them. The student can identify aims and priorities used for tasks set by him and others. The student can demonstrate the ingenuity and skill in selection of appropriate supervision appliances for selected production processes. Wydział Mechaniczny Kierunek: Mechanika i Budowa Maszyn

15 LEARNING OUTCOMES VERIFICATION AND ASSESSMENT CRITERIA: Rules for the verification of learning outcomes are presented in the table below. In the field of technical Knowledge, skills, competence sciences K_W12 K_W16 K_W22 K_U08 K_U09 K_U13 K_U15 K_K04 K_K06 The Exam. The Exam is based on written test. It is an arithmetic average from grades of written answers. The is based on realization of laboratory classes. The laboratory is determined from lab reports and from created applications. The laboratory is an arithmetic average from grades of reports and from created applications. To get a credit the student has to pass all course forms. The final grade received by the student is the arithmetic mean of the above grades. STUDENT WORKLOAD: The student workload of 125(103) hours, including work in the auditorium 45(27) hours, participate in consultations 18(9) hours, individual work 60(65) hours including preparation for classes and study reports, 30(30) hours, exam preparation 25(30) hours. Total hours of practical classes: 78(57) which corresponds to 3 ECTS Total hours of lessons with a teacher: 65(38), which corresponds to 3 ECTS RECOMMENDED READING: 1. Rząsa Mariusz R., Kiczma Bolesław : Elektryczne i elektroniczne czujniki temperatury, Wydawnictwo Komunikacji i Łączności 2005, 2. Nawrocki W.: Sensory i systemy pomiarowe, Wydawnictwo Politechniki Poznańskiej,2006, 3. Piotrowski J. i inni, Pomiary czujniki i metody pomiarowe wybranych wielkości i składu chemicznego, WNT, Warszawa 2009, 4. Podręcznik Wonderware, In Touch opisy funkcji, pól i zmiennych systemowych, Kraków 2000, 5. Podręcznik Wonderware, In Touch pierwsze kroki, Kraków 1999, 6. Podręcznik In Touch wizualizacja, USA Zakrzewski J. Czujniki i przetworniki pomiarowe podręcznik problemowy, Wydawnictwo Politechniki Śląskiej, Gliwice 2004, OPTIONAL READING: 1. Podręcznik szkoleniowy Wonderware, In Touch szkolenie podstawowe, Kraków 1998, 2. Taler D. :Pomiar ciśnienia,, prędkości i strumienia przepływu płynu, Kraków : Uczelniane Wydawnictwa Naukowo-Dydaktyczne AGH, van de Kamp Wim: Fülstandmeßtechnik in theorie und praxis, Tedopres, Dongen 1990, REMARKS: The student workloads written in brackets are the numbers for external studies. Wydział Mechaniczny Kierunek: Mechanika i Budowa Maszyn

16 Q U A L I T Y E N G I N E E R I N G Course code: 06.1-WM-MiBM-S1-AiOPP-08.1_ WM-MiBM-N1-AiOPP-08.1_09 Type of course: Language of instruction: Optional Polish Director of studies: dr inŝ. Edward Tertel Name of lecturer: dr inŝ. Edward Tertel dr inŝ. Piotr Kuryło Form of instruction tea ching hour s per semest er tea ching hour s per we ek Semest er Form of receiving a credit for a course ECTS credi ts alloca ted Full-time studies Lecture 15 1 Exam Class - - Laboratory 15 1 VII Seminar - - W orkshop - - Project - - Part-time studies 3 Lecture 9 1 Exam Class - - Laboratory 9 1 VII Seminar - - W orkshop - - Project - - COURSE AIMS: To acquaint students with the basic terms in the field of quality assurance and quality management. Knowledge of methods and the evaluation procedures of the quality evaluation of products, services and activities. Understanding the basic concepts of quality management. Acquaint with the ISO9OOO quality standards, industry standards. Discussion of basic procedures for implementing and maintaining quality management systems. PREREQUISITIES: Mathematics, Metrology, Elements of statistics, the ability to use fundamental IT-tools.

17 COURSE CONTENTS: Lecture content. The concept of quality and its definitions. Fundamental factors affecting the quality of production processes. Aspects and criteria for evaluation of the quality. The concept of quality and its definitions. Fundamental factors affecting the process and quality of production processes. Aspects and criteria for evaluation of the quality. Reliability, reliability functions. Quality systems according to the ISO series of standards, ISO 9000: basics and terminology. Quality management according to the DIN EN ISO The quality system documents. The implementation of quality management systems. Quality of processes, quality of work, quality of products quality of service. TQM - Total Quality Management objectives, concept and implementation. Six sigma - quality management by measurement of efficiency. The basic principles of Six Sigma, the implementation of the system, the use of statistical methods. Selected quality management tools. Laboratory content: Evaluation of the quality of the selected product. Determination of the reliability function for selected devices. Mapping process flow for a given production task. Elements of QMS documentation in accordance with DIN EN ISO discussion, comparative assessment. The use of selected quality management tools. Six sigma - determining of the Six Sigma quality measure for specific products/processes. Statistical Measures of Quality in the Six Sigma, setting short-term and long-term capability of the process. TEACHING METHODS: Lectures with audiovisual aids. Working with the books and journals. Individual and group work in laboratory classes. Presentation of solutions, discussion of the obtained solutions. LEARNING OUTCOMES: The reference to the learning outcomes of the field of study K_W18, K_W18 K_W18 K_U11 K_U15 K_U17 K_K02 Knowledge, skills, competence Is able to define basic concepts of quality of and quality management He can name the standards of ISO9000 family of standards, and give a short description of their subject matter. Is able to characterize elements of the QMS documentation in accordance with ISO9001. Can apply the requirements of ISO9000 to create a quality management system documentation. Is able to characterize the basic principles of quality management. Can describe the basic concepts of quality management, explain the basic differences and similarities. He can carry out an evaluation of the quality of the product by choosing appropriate evaluation criteria. Properly interprets the results. Can apply and implement the basic tools of quality management. Is aware of the consequences, both good as well as poor quality of products and processes. LEARNING OUTCOMES VERIFICATION AND ASSESSMENT CRITERIA: The verification methods for learning outcomes are presented in the table below: The reference to the learning outcomes of the field of study K_W18 K_K02 K_U11 K_U15 K_U17 K_K02 Exam, audit work The method of the learning outcomes assessment Assessment of of the course is determined on the basis of ratings for audit work (weight = 0.4) and exam (weight = 0.6). Assessment of the laboratory is based on: the laboratory exercises and reports/programs resulting from the execution of all exercises to be exercised.

18 To get a credit the student has to receive all passing grades. The final grade received by the student is the arithmetic mean of the above grades. STUDENT WORKLOAD: The student workload of 70 (70) hours, including work in the auditorium 30 (18) hours, consultations 3 (1) hours,, participations in the exam 2 (2) hours, and individual work 35 (49) hours, including: preparation for classes and preparation of reports and audit work 30 (36) hours, preparation for exam 5 (13) hours. Total hours of practical classes: 48 (46) which corresponds to 2 ECTS. Total hours of lessons with a teacher: 35 (21) which corresponds to 1 ECTS RECOMMENDED READING: 1. Hamrol Adam, Mantura Władysław: Zarządzanie jakością. Teoria i praktyka, Wydawnictwo Naukowe PWN, Hamrol Adam: Zapewnianie jakości w procesach wytwarzania, Wydawnictwo Politechniki Poznańskiej, Poznań, Praca zbiorowa, red. Tabor Adam, Zając Andrzej, Rączka Marek: Zarządzanie jakością Tom I Jakość i systemy zapewnienia jakości, Tom II Jakość w procesach wytwarzania podręcznik dla studentów wyŝszych szkół technicznych. Kraków M. Urbaniak: Zarządzanie Jakością. Teoria i praktyka, Wyd. Difin, Warszawa 2004, 5. M. Urbaniak: Systemy zarządzania w praktyce gospodarczej, Wyd. Difin, Warszawa Normy ISO serii 9000, OPTIONAL READING: 1. Miesięczniki: Problemy Jakości, Normalizacja. REMARKS: Workloads in parentheses are the numbers for part time studies.

19 O P T I M I Z A T I O N M E T H O D S Course code: 06.1-WM-MiBM-S1-AiOPP-10_ WM-MiBM-N1-AiOPP-10_12 Type of course: Language of instruction: Compulsory Polish Director of studies: Prof. dr hab. inŝ. Mirosław Galicki Prof. dr hab. inŝ. M. Galicki Name of lecturer: dr inŝ. Piotr Kuryło dr inŝ. Edward Tertel Form of instruction tea ching hour s per semest er tea ching hour s per we ek Semest er Form of receiving a credit for a course ECTS credi ts alloca ted Full-time studies Lecture 30 2 Class - - Laboratory 30 2 VII Seminar - - W orkshop - - Project - - Part-time studies 2 Lecture 18 2 Class - - Laboratory 18 2 VII Seminar - - W orkshop - - Project - - COURSE AIMS: Acquainting students with the basic terms and definitions in the field of optimization, the essence of optimization, mathematical basis of optimization. Identify methods and tools for solving optimization problems, with particular reference to applications in mechanics and mechanical engineering. PREREQUISITIES:

20 The mathematical analysis, elements of the theory of probability, the ability to use IT tools: spreadsheets, Matlab / Scilab. COURSE CONTENTS: Lecture content. The properties of extremes of multivariable functions. Extremes of function without the constraint. Extremes function with the constraints of equality. The method of Lagrange multipliers. Extremes functions with the constraints limiting inequality. Regularity and irregularity. Dual task of optimization. Linear functions with linear constraint. The dual linear optimization task. Simplex method to solve the linear programming problem. Gradient algorithms for determine the minimum of functions without the constraints. The methods of finding the minimum point at restrictive conditions. Finding extreme points of the function in the presence of noise. Laboratory content: MATLAB / Scilab-tools to perform engineering and scientific calculations and presenting the results of calculations. Solving the "simple" tasks of optimization with two decision variables by the graphical method - discrete optimization. Formulating a mathematical description of ZPL. The use of tools such as SOLVER to solve the ZPL. Solving the ZPL using SYMPLEX method - filling simplex tables, the use of ready-made programs. Nonlinear Optimization - sample application programs, comparing the effectiveness of different methods of nonlinear optimization. TEACHING METHODS: Lectures with audiovisual aids. Working with the journals. Individual and group work in laboratory classes. Presentation of solutions, discussion of the obtained solutions. LEARNING OUTCOMES: The reference to the learning outcomes of the field of study K_W22 K_W01 K_W22 K_U09 K_U16 K_K04 K_U13 K_U17 K_U17 K_K01 Knowledge, skills, competence The student is able to define the basic concepts of optimization and give a name and a short description the types of optimization. He can to formulate a mathematical description of optimization tasks. He can analyze the optimization task and apply the appropriate method to solve it. Is able to solve a linear programming problems using a variety of methods and tools, in particular IT-tools. He can critically evaluate the results of optimization. It is open to the use of different tools to solve optimization tasks LEARNING OUTCOMES VERIFICATION AND ASSESSMENT CRITERIA: The verification methods for learning outcomes are presented in the table below: The reference to the learning outcomes of the field of study K_W01 K_W22 K_W01 K_W22 K_U09 K_U13 K_U16 K_U17 K_K01 Written test The method of the learning outcomes assessment Assessment of the laboratory is based on: the laboratory exercises and reports/programs resulting from the execution of all exercises to be exercised.

21 K_K04 To get a credit the student has to receive all passing grades. The final grade received by the student is the arithmetic mean of the above grades. STUDENT WORKLOAD: The student workload of 66 (52) hours, including work in the auditorium 60 (36) hours, individual work 6 (16) hours, including: preparation for classes and preparation of reports 4 (10) hours, preparation for the written test 2 (6) hours. Total hours of practical classes: 34 (28) which corresponds to 1 ECTS. Total hours of lessons with a teacher: 60 (36) which corresponds to 1 ECTS RECOMMENDED READING: 1. Brdyś M., Ruszczyński A., Metody optymalizacji w zadaniach. Warszawa, WNT, 1985, 2. Findeisen W., Szymanowski J., Wierzbicki A., Teoria i metody obliczeniowe optymalizacji. Warszawa, PWN, 1980, 3. Seidler J., Badach A., Molisz W., Metody rozwiązywania zadań optymalizacji. Warszawa, Podręczniki Akademickie, OPTIONAL READING: 1. Koronacki J., Aproksymacja stochastyczna: metody optymalizacji w warunkach losowych. Warszawa, WNT, 1989 REMARKS: Workloads in parentheses are the numbers for part time studies.