COURSE INTRODUCTION AND APPLICATION INFORMATION

ce.cs.ieu.edu.tr

Course Name

Code	Semester	Theory (hour/week)	Application/Lab (hour/week)	Local Credits	ECTS
	Fall/Spring

Prerequisites	None
Course Language
Course Type	Elective
Course Level	-
Mode of Delivery	-
Teaching Methods and Techniques of the Course
Course Coordinator	-
Course Lecturer(s)	-
Assistant(s)	-

Course Objectives
Learning Outcomes	The students who succeeded in this course; Will be able to define the meaning and scope of Stochastic Models in Manufacturing in a historical context Will be able to understand important metrics that specify a system’s performance Will be able to become familiar with Queueing Networks and their applications Will be able to understand the scope of variety of queueing models such as M/M/1, M/G/1, GI/G/1 and Open and Closed Networks Will be able to analyze real life examples which aims to improve the manufacturer's productivity and efficiency through better design
Course Description

Course Category	Core Courses
	Major Area Courses	X
	Supportive Courses
	Media and Managment Skills Courses
	Transferable Skill Courses

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week	Subjects	Required Materials
1	Introduction: Basics of Probability	3
2	Markov Chains and Processes	2
3	The M/M/1 Queue	2
4	Transfer Lines Models and Bounds	1
5	Transfer Lines Models and Bounds (Continue)	1
6	Deterministic Processing Time Transfer Line – 2 Machine	1
7	Deterministic Processing Time Transfer Line – 2 Machine (Continue)	1
8	Exponential Processing Time Transfer Line – 2 Machine	1,2,3
9	Exponential Processing Time Transfer Line – 2 Machine (Continue)	1,2,3
10	Exponential Processing Time Transfer Line – 2 Machine (Continue)	1,2,3
11	Deterministic Processing Time Transfer Line – Many Machines	1,2
12	Deterministic Processing Time Transfer Line – Long Line Optimization	1,2
13	Stochastic Long Lines	1,2
14	Stochastic Long Lines	1,2
15	Assembly – Disassembly Systems	1,2
16	Review of the Semester

Course Notes/Textbooks

The Course Material can be reached thru Course Web Pages.

Suggested Readings/Materials

Ana Ders Kitabı / Main Text Book : 1.Gershwin, Stanley B. Manufacturing Systems Engineering. Paramus NJ: Prentice Hall, 1993. ISBN: 9780135606087. or Manufacturing Systems Engineering, Stanley B. Gershwin, 2002. (gershwin@mit.edu, http://web.mit.edu/manufsys/www) Yardımcı Kitaplar / Supplementary References : 2. Stochastic Models of Manufacturing Systems, John A. Buzacott and J. George Shanthikumar, Prentice Hall, 1993. ISBN: 9780138475673 3. Production Systems Engineering, Jingshang Li and Semyon Meerkov, Springer, 2009. ISBN: 9780387755786

EVALUATION SYSTEM

Semester Activities	Number	Weigthing
Participation	1 – 15	5
Laboratory / Application
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments	5	10
Presentation / Jury
Project	1	20
Seminar / Workshop
Oral Exam
Midterm	1	25
Final Exam	1	40
Total

Weighting of Semester Activities on the Final Grade		60
Weighting of End-of-Semester Activities on the Final Grade		40
Total

ECTS / WORKLOAD TABLE

Semester Activities	Number	Duration (Hours)	Workload
Course Hours (Including exam week: 16 x total hours)	16	3	48
Laboratory / Application Hours (Including exam week: 16 x total hours)	16
Study Hours Out of Class
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments	5	3
Presentation / Jury
Project	1	52
Seminar / Workshop
Oral Exam
Midterms	1	2
Final Exams	1	3
		Total	120

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#	Program Competencies/Outcomes	* Contribution Level
#	Program Competencies/Outcomes	1	2	3	4	5
1	Adequate knowledge in Mathematics, Science and Computer Engineering; ability to use theoretical and applied information in these areas to model and solve Computer Engineering problems				X
2	Ability to identify, define, formulate, and solve complex Computer Engineering problems; ability to select and apply proper analysis and modeling methods for this purpose			X
3	Ability to design a complex computer based system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; ability to apply modern design methods for this purpose		X
4	Ability to devise, select, and use modern techniques and tools needed for Computer Engineering practice		X
5	Ability to design and conduct experiments, gather data, analyze and interpret results for investigating Computer Engineering problems			X
6	Ability to work efficiently in Computer Engineering disciplinary and multi-disciplinary teams; ability to work individually			X
7	Ability to communicate effectively in Turkish, both orally and in writing; knowledge of a minimum of two foreign languages
8	Recognition of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself
9	Awareness of professional and ethical responsibility
10	Information about business life practices such as project management, risk management, and change management; awareness of entrepreneurship, innovation, and sustainable development
11	Knowledge about contemporary issues and the global and societal effects of engineering practices on health, environment, and safety; awareness of the legal consequences of Computer Engineering solutions

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest