IE 338 | Course Introduction and Application Information - Department of Industrial Engineering

Course Name

Stochastic Models in Manufacturing Systems

Code	Semester	Theory (hour/week)	Application/Lab (hour/week)	Local Credits	ECTS
IE 338	Fall/Spring	3	0	3	6

Prerequisites

IE 353 To succeed (To get a grade of at least DD)

Course Language

English

Course Type

Elective

Course Level

First Cycle

Mode of Delivery

-

Teaching Methods and Techniques of the Course

Lecture / Presentation

National Occupation Classification

-

Course Coordinator

Dr. Öğr. Üyesi Kamil Erkan Kabak

Course Lecturer(s)

Dr. Öğr. Üyesi Kamil Erkan Kabak

Assistant(s)

-

Course Objectives

The objective of this course is to purvey for the students of the following:Describe some important issues in the design and operation of manufacturing systems. Explain important measures of system performance. Show the importance of random, potentially disruptive events. Give some intuition about behavior of these systems. Explain the importance of capacity, and how it can vary randomly over time.

Learning Outcomes

#	Content	PC Sub	* Contribution Level
#	Content	PC Sub	1	2	3	4	5
1	to define the meaning and scope of Stochastic Models in Manufacturing in a historical context
2	to explain important metrics that specify a system’s performance
3	to give examples from Queueing Networks and their applications
4	to explain the scope of variety of queueing models such as M/M/1, M/G/1, GI/G/1 and Open and Closed Networks
5	to analyze real life examples which aims to improve the manufacturer's productivity and efficiency through better design

Course Description

This course deals with the following topics: Models of manufacturing systems, including transfer lines and flexible manufacturing systems; Calculation of performance measures, including throughput, inprocess inventory, and meeting production commitments; Realtime control of scheduling; Effects of machine failure, setups, and other disruptions on system performance.

Related Sustainable Development Goals

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

Week	Subjects	Related Preparation	Learning Outcome
1	Introduction: Basics of Probability	Lii J., and Meerkov, S. Production Systems Engineering, Ch 1, Springer, 2009.
2	Markov Chains and Processes	Buzacott, J.A and Shanthikumar, J. G. Stochastic Models of Manufacturing Systems, Ch 3, Prentice Hall, 1993
3	The M/M/1 Queue	Buzacott, J.A and Shanthikumar, J. G. Stochastic Models of Manufacturing Systems, Ch 3, Prentice Hall, 1993
4	Transfer Lines Models and Bounds	Buzacott, J.A and Shanthikumar, J. G. Stochastic Models of Manufacturing Systems, Ch 3, Prentice Hall, 1993
5	Transfer Lines Models and Bounds (Continue)	Gershwin, Stanley B. Manufacturing Systems Engineering. Ch 2, Paramus NJ: Prentice Hall, 1993.
6	Deterministic Processing Time Transfer Line – 2 Machine	Gershwin, Stanley B. Manufacturing Systems Engineering. Ch 2, Paramus NJ: Prentice Hall, 1993.
7	Deterministic Processing Time Transfer Line – 2 Machine (Continue)	Gershwin, Stanley B. Manufacturing Systems Engineering. Ch 2, Paramus NJ: Prentice Hall, 1993.
8	Exponential Processing Time Transfer Line – 2 Machine	Gershwin, Stanley B. Manufacturing Systems Engineering, Ch 3, Paramus NJ: Prentice Hall, 1993. Buzacott, J.A and Shanthikumar, J. G. Stochastic Models of Manufacturing Systems, Ch 3. Prentice Hall, 1993. Lii J., and Meerkov, S. Production Systems Engineering, Springer, Ch 3, 2009.
9	Exponential Processing Time Transfer Line – 2 Machine (Continue)	Gershwin, Stanley B. Manufacturing Systems Engineering, Ch 3,. Paramus NJ: Prentice Hall, 1993. Buzacott, J.A and Shanthikumar, J. G. Stochastic Models of Manufacturing Systems, Ch 3, Prentice Hall, 1993 Lii J., and Meerkov, S. Production Systems Engineering, Springer, 2009.
10	Exponential Processing Time Transfer Line – 2 Machine (Continue)	Gershwin, Stanley B. Manufacturing Systems Engineering, Ch 3, Paramus NJ: Prentice Hall, 1993. Buzacott, J.A and Shanthikumar, J. G. Stochastic Models of Manufacturing Systems, Ch 3, Prentice Hall, 1993 Lii J., and Meerkov, S. Production Systems Engineering, Springer, C2009.
11	Deterministic Processing Time Transfer Line – Many Machines	Gershwin, Stanley B. Manufacturing Systems Engineering, Ch 3, Paramus NJ: Prentice Hall, 1993. Buzacott, J.A and Shanthikumar, J. G. Stochastic Models of Manufacturing Systems, Prentice Hall, Ch 3, 1993
12	Deterministic Processing Time Transfer Line – Long Line Optimization	Gershwin, Stanley B. Manufacturing Systems Engineering, Ch 3,Paramus NJ: Prentice Hall, 1993. Buzacott, J.A and Shanthikumar, J. G. Stochastic Models of Manufacturing Systems, Prentice Hall, 1993
13	Stochastic Long Lines	Gershwin, Stanley B. Manufacturing Systems Engineering, Ch 3, Paramus NJ: Prentice Hall, 1993. Buzacott, J.A and Shanthikumar, J. G. Stochastic Models of Manufacturing Systems, Prentice Hall, Ch 3, 1993
14	Stochastic Long Lines	Gershwin, Stanley B. Manufacturing Systems Engineering, Ch 3, Paramus NJ: Prentice Hall, 1993. Buzacott, J.A and Shanthikumar, J. G. Stochastic Models of Manufacturing Systems, Prentice Hall, Ch 3, 1993
15	Review of the semester
16	Final Exam

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

Semester Activities	Number	Weigthing	LO 1	LO 2	LO 3	LO 4	LO 5
Participation	1 – 15	5
Laboratory / Application
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments	5	10
Presentation / Jury
Project	1	20
Seminar / Workshop
Oral Exams
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

Semester Activities	Number	Duration (Hours)	Workload
Theoretical Course Hours (Including exam week: 16 x total hours)	16	3	48
Laboratory / Application Hours (Including exam week: '.16.' x total hours)	16		0
Study Hours Out of Class	14	3	42
Field Work			0
Quizzes / Studio Critiques			0
Portfolio			0
Homework / Assignments	5	4	20
Presentation / Jury			0
Project	1	20	20
Seminar / Workshop			0
Oral Exam			0
Midterms	1	20	20
Final Exam	1	30	30
		Total	180

#	PC Sub	Program Competencies/Outcomes	* Contribution Level
#	PC Sub	Program Competencies/Outcomes	1	2	3	4	5
1	To have adequate knowledge in Mathematics, Science and Industrial Engineering; to be able to use theoretical and applied information in these areas to model and solve Industrial Engineering problems.		-	X	-	-	-
2	To be able to identify, formulate and solve complex Industrial Engineering problems by using state-of-the-art methods, techniques and equipment; to be able to select and apply proper analysis and modeling methods for this purpose.		-	-	X	-	-
3	To be able to analyze a complex system, process, device or product, and to design with realistic limitations to meet the requirements using modern design techniques.		-	-	-	-	X
4	To be able to choose and use the required modern techniques and tools for Industrial Engineering applications; to be able to use information technologies efficiently.		-	-	X	-	-
5	To be able to design and do simulation and/or experiment, collect and analyze data and interpret the results for investigating Industrial Engineering problems and Industrial Engineering related research areas.		X	-	-	-	-
6	To be able to work efficiently in Industrial Engineering disciplinary and multidisciplinary teams; to be able to work individually.		X	-	-	-	-
7	To be able to communicate effectively in Turkish, both orally and in writing; to be able to author and comprehend written reports, to be able to prepare design and implementation reports, to present effectively; to be able to give and receive clear and comprehensible instructions		-	-	-	-	-
8	To have knowledge about contemporary issues and the global and societal effects of Industrial Engineering practices on health, environment, and safety; to be aware of the legal consequences of Industrial Engineering solutions.		-	-	-	-	-
9	To be aware of professional and ethical responsibility; to have knowledge of the standards used in Industrial Engineering practice.		-	-	-	-	-
10	To have knowledge about business life practices such as project management, risk management, and change management; to be aware of entrepreneurship and innovation; to have knowledge about sustainable development.		-	-	-	-	-
11	To be able to collect data in the area of Industrial Engineering; to be able to communicate with colleagues in a foreign language.		-	-	-	-	-
12	To be able to speak a second foreign at a medium level of fluency efficiently.		-	-	-	-	-
13	To recognize the need for lifelong learning; to be able to access information, to be able to stay current with developments in science and technology; to be able to relate the knowledge accumulated throughout the human history to Industrial Engineering.		-	-	-	-	-