ECTS
ECTS Course Catalogue
Course details
Course code: RIPS10006o15Semester: 2015/2016 summer
Name: Informatics and computer aided engineering I
Major: Production Engineering and Management
Study Type: first cycle
Course type: compulsory
Study Semester: 2
ECTS points: 2
Hours (Lectures / Tutorials / Other): 15 / 30 / 0
Lecturer: dr inż. Krzysztof Lejman, dr Wojciech Jakubowski, dr inż. Krzysztof Pieczarka
Language of instruction: Polish / English
Learning outcomes: Knowledge: Students acquire theoretical and practical knowledge of applied mathematics, computer science, engineering mechanics, engineering graphics engineering and statistics in solving engineering problems. Identifies the method of experiment planning and the practical application of statistical tools and statistical inference. He has knowledge of the structure of relational databases, understands the importance of normalization of the database, he can write a SQL statement, these editing and search the existing relational database. He knows the structure of computer networks and network applications, knows the basics of designing a solid and substantial basis for process design detail in the machine processing of numerical. Skills: The student acquires the ability to apply mathematical methods and statistical information supporting engineering. Acquires the ability to draw conclusions based on the results of statistical analyzes measuring the material. Students planning to experiment with the use of information technology. Distinguishes between mathematical and statistical methods in terms of their use in the art. Distinguishes between the concept of advanced statistical and mathematical methods. Able to choose appropriate methods and technologies to solve problems, depending on the variables of tasks. The student has the ability to recognize the construction of a relational database structure, can result in the normalization and to formulate a simple query in SQL queries. Student knows how to make a simple web application using Visual Studio program. Able to design a simple detail in the module "part" using the program SolidEdge and can design stages of his treatment with the NXCAM
Competences: The student demonstrates an understanding of advanced statistical methods for analysis and inference in the test area. Recognizes the principles of proper presentation of results and justifies the correctness of the methods used. Assess and explain the results of analyzes carried out using statistical tools and information. It shows the need for self-improvement and training in the use of modern information technology based on the practical applications of mathematics, statistics, graphics, engineering and mechanics. Demonstrates knowledge and understanding of issues relating to the operation of databases and use them in practice. Defines the purpose of the project and committed to its implementation, working independently of the execution of individual tasks, discussing the chosen methods of project implementation
Prerequisites: mathematics, information technology, material science, design engineering and engineering graphics
Course content: Planning an Experiment and statistical inference, data management, text and numeric, preparing data for analysis and visualization using a variety of presentation techniques, standard and modified graphical procedure, the cooperation of statistical programs of word processing and presentational software. Using elementary logic to solve engineering problems. Flat-file databases and relational. Relational database schema. Relational database management. Normalization of relational schema. Native SQL. The structure of an application in ASP.NET. Solid design with CAD programs. Workpiece machining process design CAM software enhanced.
Recommended literature: 1. Augustyn K. 2009. NX CAM. Programowanie ścieżek dla obrabiarek CNC. Wyd. Helion. 2. Cristian Darie, Zak Ruvalcaba 2007. ASP.NET 2.0. Tworzenie witryn internetowych z wykorzystaniem C# i Visual Basica. Wyd. Helion 3. Dokumentacja wybranych systemów zarządzania relacyjnymi bazami danych 4. Hernandez M. J. (2004).Bazy danych dla zwykłych śmiertelników. Wydawnictwo Mikom. 5. Kala R. Statystyka dla przyrodników. Wyd. AR Poznań, 2002. 6. Kazimierczak G., Pacula B., Budzyński B. 2004. Solid Edge. Komputerowe wspomaganie projektowania. Wyd. Helion. 7. Koronacki J., Mielniczuk J.: Statystyka dla studentów kierunków technicznych i przyrodniczych. WNT, 2001. 8. Leszek W.: Badania empiryczne – wybrane zagadnienia metodyczne, Wydawnictwo Instytutu Technologii Eksploatacji, Radom, 1997 9. Łomnicki A.: Wprowadzenie do statystyki dla przyrodników. PWN, Warszawa 2003 10. Pabis S.: Metodologia i metody nauk empirycznych, PWN, Warszawa, 1985 11. Statistica PL, Tom I – Ogólne konwencje i statystyki, Tom II – Grafika, Tom III – Statystyki II, StatSoft Polska Sp. z o.o., Kraków, 1997 12. Trętowski J., Wójcik A. R.: Metodyka doświadczeń rolniczych, Wydawnictwa Uczelniane WSRP w Siedlcach, 1991 13. Volk V.: Statystyka stosowana dla inżynierów, WNT, Warszawa, 1973
Assessment methods: Assessment of learning outcomes in terms of knowledge: colloquia on exercises Assessment of learning outcomes in literacy: assessment alone resolved statistical analysis, to assess the ability of selection tools for solving engineering and process simulation, evaluation of the correctness of the choice of visualization. Skills assessment and selection of statistical methods of statistical inference to changing tasks. Checking the ability to build SQL queries-those. Skills assessment application
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