Information Package / Course Catalogue
| Computer Engineering | |||||
| Bachelor | Length of the Programme: 4 | Number of Credits: 240 | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF: Level 6 |
Ders Genel Tanıtım Bilgileri
| School/Faculty/Institute | Faculty of Engineering | |||||||||
| Course Code | IE 304 | |||||||||
| Course Title in English | Simulation | |||||||||
| Course Title in Turkish | Simülasyon | |||||||||
| Language of Instruction | EN | |||||||||
| Type of Course | Flipped Classroom | |||||||||
| Level of Course | Select | |||||||||
| Semester | ||||||||||
| Contact Hours per Week |
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| Estimated Student Workload | 155 hours per semester | |||||||||
| Number of Credits | 6 ECTS | |||||||||
| Grading Mode | Standard Letter Grade | |||||||||
| Pre-requisites |
MATH 222 - Probability and Statistics for Engineering II | MATH 228 - Probability and Statistics for Engineering II |
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| Expected Prior Knowledge | Basic probability and statistics knowledge | |||||||||
| Co-requisites | None | |||||||||
| Registration Restrictions | MATH 228 | |||||||||
| Overall Educational Objective | To learn the basic simulation modeling and programming concepts | |||||||||
| Course Description | This is a hands-on course on simulation for undergraduate students. The course includes simulation modeling and programming in general-purpose languages. The use of simulation for estimation, comparison of alternatives and optimization will be addressed. The course covers random number generation and testing, input data analysis, simulation model validation and verification, discrete event simulation, statistical output analysis and experimental design. | |||||||||
| Course Description in Turkish | Lisans öğrencileri için uygulamalı bir simülasyon dersidir. Genel-amaçlı diller kullanarak simülasyon modelleme ve programlamayı içerir. Tahmin, alternatiflerin karşılaştırılması ve optimizasyon için simülasyonun kullanımı anlatılacaktır. Bu ders şu konuları içerir; rassal sayı yaratma ve test etme, girdi verisi analizi, simülasyon model doğrulama ve kanıtlama, ayrık vaka simülasyonu, istatistiksel çıktı analizi ve deney tasarımı. |
Course Learning Outcomes and CompetencesUpon successful completion of the course, the learner is expected to be able to:1) understand basic concepts in real systems to translate them into simulation models; 2) design conceptual representations of real systems to describe simulation models; 3) validate and verify discrete event simulation models using modern tools; 4) analyze and compare simulation outputs using statistical tools; 5) create what-if scenarios for evaluating alternatives for the systems models are built; 6) conduct experiments in simulation according to established procedures and report the results; 7) function effectively as a member of a team; organize and deliver effective verbal, written, virtual, and graphical communications; 8) suggesting solution alternatives for problems in systems and creating and evaluating performance metrics; 9) expressing simulation models and their outputs with different levels of detail for user needs; 10) transforming, analyzing and interpreting data collected for simulation model building. |
| Program Learning Outcomes/Course Learning Outcomes | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 |
|---|---|---|---|---|---|---|---|---|---|---|
| 1) An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics | ||||||||||
| 2) An ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors | ||||||||||
| 3) An ability to communicate effectively with a range of audiences | ||||||||||
| 4) An ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts | ||||||||||
| 5) An ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives | ||||||||||
| 6) An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions | ||||||||||
| 7) An ability to acquire and apply new knowledge as needed, using appropriate learning strategies. |
Relation to Program Outcomes and Competences
| N None | S Supportive | H Highly Related |
| Program Outcomes and Competences | Level | Assessed by | |
| 1) | An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics | H | Exam,Project |
| 2) | An ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors | H | Project |
| 3) | An ability to communicate effectively with a range of audiences | H | Presentation,Project |
| 4) | An ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts | S | Exam,Project |
| 5) | An ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives | H | Project |
| 6) | An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions | H | Exam,Project |
| 7) | An ability to acquire and apply new knowledge as needed, using appropriate learning strategies. | S | Project |
| Prepared by and Date | UTKU KOÇ , December 2020 |
| Course Coordinator | UTKU KOÇ |
| Semester | |
| Name of Instructor | Asst. Prof. Dr. UTKU KOÇ |
Course Contents
| Week | Subject |
| 1) | Introduction to simulation modeling |
| 2) | Random number generation |
| 3) | Testing random number generators |
| 4) | Random variate generation |
| 5) | Input data analysis |
| 6) | Simulation model validation and verification |
| 7) | Discrete Event Simulation using software (basic operations) |
| 8) | Discrete Event Simulation using software (detailed operations) |
| 9) | Discrete Event Simulation using software (intermediate modeling) |
| 10) | Discrete Event Simulation using software (Entity Transfer) |
| 11) | Statistical output analysis for terminating simulations |
| 12) | Statistical output analysis for steady state simulations |
| 13) | Experimental design and simulation optimization |
| 14) | Project presentations |
| 15) | Final Exam/Project Presentation Period |
| 16) | Final Exam/Project Presentation Period |
| Required/Recommended Readings | • Kelton, W. D., Sadowski, R. P., and Zupick, N. B., Simulation with Arena, 6th Ed., McGraw Hill, 2015 • Banks, J., Carson, J. S., Nelson, B. L., and Nicol, D. M., Discrete-Event System Simulation, 4th Ed., Prentice Hall, 2005 - J.Shalliker, C.Ricketts (2009) An Introduction to Simulation in the Manufacturing Industry using SIMUL8 2008. E-Book. | ||||||||||||||||||
| Teaching Methods | Lectures/contact hours using “flipped classroom” as an active learning technique/Implementation at a Computer Laboratory | ||||||||||||||||||
| Homework and Projects | A complete simulation project will be completed in groups of students | ||||||||||||||||||
| Laboratory Work | Implementation of the methods learned in class | ||||||||||||||||||
| Computer Use | SIMUL8 software | ||||||||||||||||||
| Other Activities | |||||||||||||||||||
| Assessment Methods |
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| Course Administration |
Exams and quizzes: Closed book and closed notes. Homework: N/A Rules for attendance: YÖK regulations. You are responsible for the announcements made in class. Rules for late submission of assignments: N/A Missing a quiz: No make-up will be given for the missed quizzes. For certain excuses (decided by the instructor) the percentage of the missed quiz may be added to the midterm or to the final. Missing a midterm: You are expected to be present without exception and to plan any travel around these dates accordingly. Medical emergencies are of course excluded if accompanied by a doctor’s note. A note indicating that you were seen at the health center on the day of the exam is not a sufficient documentation of medically excused absence from the exam. The note must say that you were medically unable to take the exam. Provided that proper documents of excuse are presented, missed midterm by the student will be given the grade of the final exam. No make-up will be given. If you fail to take the exam on the assigned day and do not have a valid excuse, you will be given zero (0) on the exam. Employment interviews, employer events, weddings, vacations, etc. are not excused absences. Eligibility to take the final exam: YÖK regulations. Missing a final: Faculty regulations. A reminder of proper classroom behavior, code of student conduct: YÖK Regulations Statement on plagiarism: YÖK Regulations (http://3fcampus.mef.edu.tr/uploads/cms/webadmin.mef.edu.tr/4833_2.pdf) |
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ECTS Student Workload Estimation
| Activity | No/Weeks | Hours | Calculation | ||||
| No/Weeks per Semester | Preparing for the Activity | Spent in the Activity Itself | Completing the Activity Requirements | ||||
| Course Hours | 14 | 1 | 3 | 56 | |||
| Laboratory | 14 | 1 | 1 | 28 | |||
| Project | 1 | 20 | 1 | 21 | |||
| Quiz(zes) | 4 | 3 | 1 | 16 | |||
| Midterm(s) | 1 | 10 | 2 | 12 | |||
| Final Examination | 1 | 20 | 2 | 22 | |||
| Total Workload | 155 | ||||||
| Total Workload/25 | 6.2 | ||||||
| ECTS | 6 | ||||||