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IE 441

Course ID:
Course Code & Number
IE 441
Course Title
Stochastic Processes
Level
BS
Credit Hours/ ECTS Credits
(3+0+0) 3 TEDU Credits, 5 ECTS Credits
Year of Study:
Senior
Semester:
Type of Course:
Elective
Mode of Delivery:
Face-to-face
Language of Instruction:
Pre-requisite / Co-requisite::
Pre-requisites: IE 332
Co-requisites: NONE
Catalog Description
Introduction to stochastic processes. Conditional expectation. Poisson processes. Markov processes.
Course Objectives

The goal of this course is to teach descriptive models to random events arising in manufacturing and service operations. The models covered are Poisson processes, renewal theory, and discrete and continuous time Markov chains. The course also presents the applications of stochastic processes to solve engineering related problems.

Software Usage
Course Learning Outcomes

Upon succesful completion of this course, a student will be able to
1. Describe a stochastic process (B1, a1)
2. Analyze and identify a stochastic process (B4, e)
3. Generate stochastic models to describe random events in production systems (B5, c)
4. Critically assess the use of stochastic processes in solving complex contemporary problems of manufacturing and service systems (B6, h)
5. Recognize the need of and engage in life-long learning (i)

Learning Activities and Teaching Methods:
Telling/Explaining Discussion/Debate Reading Case Study/Scenarion Analysis Simulation & Games
Assessment Methods and Criteria:
Test / Exam Quiz Case Studies / Homework
Assessment Methods and Criteria Others:
Design Content
Recommended Reading
Required Reading
S.M. Ross, Stochastic Processes. Wiley. 1995
Grading
Learning Activities and Teaching Methods Others:
Course Coordinator:
Student Workload:
WorkloadHrs
Course & Program Learning Outcome Matching: