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| END3016 | Simulation | 3+0+0 | ECTS:5 | | Year / Semester | Spring Semester | | Level of Course | First Cycle | | Status | Compulsory | | Department | DEPARTMENT of INDUSTRIAL ENGINEERING | | Prerequisites and co-requisites | DC must have been achieved from END2010-Engineering Statistics - II | | Mode of Delivery | Face to face | | Contact Hours | 14 weeks - 3 hours of lectures per week | | Lecturer | Dr. Öğr. Üyesi Kadir BÜYÜKÖZKAN | | Co-Lecturer | Non | | Language of instruction | Turkish | | Professional practise ( internship ) | None | | | | The aim of the course: | | To gain skill to statistical data analysis
To gain skill to develop simulation models
To gain skill to experiment with the simulation model and to analyze experiment results |
| Learning Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | LO - 1 : | Design and conduct experiments,to analyze and interpret experiment results | 1,2,3,6,11,12 | | | LO - 2 : | Ability to design to meet the requirements of a system, component or process to meet skills | 1,2,5,11,12 | | | LO - 3 : | Ability to identify, formulate and solve engineering problems | 1,2,3,5,11,12 | | | CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam, 3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation, 6: Term paper), LO : Learning Outcome | | |
| Statistical data analysis, develop simulation models, experiment with the simulation model and to
analyze experiment results. |
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| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | Definitions, simulation, system model, simulation types, advantages and disadvantages of simulation, Application areas | | | Week 2 | Monte Carlo method and simulation languages | | | Week 3 | Queuing systems, discrete event simulation, time advance and manual simulation | | | Week 4 | Point statistics, parameter estimates and fitness tests in determining the input probability distributions | | | Week 5 | Point statistics, parameter estimates and fitness tests in determining the input probability distributions | | | Week 6 | Introduction to simulation language ARENA, ARENA Simulation Languages basic modeling concepts | | | Week 7 | Advanced modeling with simulation language ARENA | | | Week 8 | Advanced modeling with simulation language ARENA | | | Week 9 | Midterm | | | Week 10 | Random number of features and production, inverse transform technique in the production of random variables, Reject technique in the random variable production | | | Week 11 | Output Analysis, Output analysis for terminated simulation | | | Week 12 | Output Analysis, Output analysis for non finish simulation | | | Week 13 | Comparison of the alternative system, | | | Week 14 | Variance reduction techniques | | | Week 15 | Make-up exam | | | Week 16 | Final | | | |
| 1 | Law,AM,2007,Simulation Modelling and Analysis,McGraw Hill Kelton, | | | |
| Method of Assessment | | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | | Mid-term exam | 9 | | | 40 | | Project | 11 | | | 10 | | End-of-term exam | 16 | | | 50 | | |
| Student Work Load and its Distribution | | Type of work | Duration (hours pw) | No of weeks / Number of activity | Hours in total per term | | Yüz yüze eğitim | 3 | 14 | 42 | | Sınıf dışı çalışma | 2 | 14 | 28 | | Arasınav için hazırlık | 5 | 1 | 5 | | Arasınav | 2 | 1 | 2 | | Proje | 10 | 1 | 10 | | Dönem sonu sınavı için hazırlık | 5 | 1 | 5 | | Dönem sonu sınavı | 2 | 1 | 2 | | Total work load | | | 94 |
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