INDUSTRIAL ENGINEERING (ENGLISH, PHD)
PhD	TR-NQF-HE: Level 8	QF-EHEA: Third Cycle	EQF-LLL: Level 8

Course Introduction and Application Information

Course Code	Course Name	Semester	Theoretical	Practical	Credit	ECTS
INE6360	Special Topics in Demand Planning	Fall Spring	3	0	3	9

This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

Language of instruction:	English
Type of course:	Departmental Elective
Course Level:
Mode of Delivery:
Course Coordinator :	Assoc. Prof. BARIŞ SELÇUK
Recommended Optional Program Components:	None
Course Objectives:	CO 1: to recognize the quantitative techniques for time series forecasting CO 2: be able to measure forecasting errors CO 3: be able to perform regression analysis CO 4: be able to use casual forecasting methods CO 5: understand the relationship between demand planning and other business units such as sales, logistics, capacity planning

Learning Outcomes

The students who have succeeded in this course;
In todays highly complex and competitive business arena, there is an increasing pressure on management profesionals to face predictable demand, because all the other operations in a company depends on sales forecasts. In this course, the topic of demand planning is treated from a perspective that is broader than just statistical forecasting by considering the interaction between different business units such as marketing, logistics, capacity planning and etc. Demand management techniques are analyzed from a modeling perspective.

Course Content

Weekly Detailed Course Contents

Week	Subject	Related Preparation
1)	Introduction Chp 1,2
2)	Introduction Chp 3
3)	Forecasting Methods Chp 4
4)	Quantitative forecasting methods using time series data Chp 5
5)	Quantitative forecasting methods using time series data Chp 5
6)	Quantitative forecasting methods using time series data Chp 5
7)	Quantitative forecasting methods using time series data Chp 5
8)	Midterm
9)	Quantitative forecasting methods using casual data Chp 6
10)	Quantitative forecasting methods using casual data Chp 6
11)	Weighted combined forecasting methods Chp 7
12)	Weighted combined forecasting methods Chp 7
13)	Term Project Presentations
14)	Term Project Presentations

Sources

Course Notes / Textbooks:	Demand driven forecasting: A structural approach to forecasting Charles Chase 2009
References:

Evaluation System

Semester Requirements	Number of Activities	Level of Contribution
Total		%
PERCENTAGE OF SEMESTER WORK		% 0
PERCENTAGE OF FINAL WORK		%
Total		%

Contribution of Learning Outcomes to Programme Outcomes

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

	Program Outcomes	Level of Contribution
1)	Follows the scientific literature, analyzes it critically, and uses it effectively in solving engineering problems.
2)	Designs, plans, implements, and manages original projects related to the program field.
3)	Independently conducts studies related to the program field, assumes scientific responsibility, and evaluates the results with a critical perspective.
4)	Presents the results of their research and projects effectively in written, oral, and visual formats in accordance with academic standards.
5)	Conducts independent research on subjects requiring expertise in their field, develops original ideas, and transfers this knowledge into practice.
6)	Effectively uses advanced theoretical and practical knowledge specific to the program field.
7)	Acts in accordance with professional, scientific, and ethical values; takes responsibility by considering the social, environmental, and ethical impacts of engineering practices.