COURSE UNIT TITLE

: DATA ANALYTICS FOR OPERATIONS MANAGEMENT

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
DSM 5010 DATA ANALYTICS FOR OPERATIONS MANAGEMENT ELECTIVE 3 0 0 8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

ASSOCIATE PROFESSOR UMAY ZEYNEP UZUNOĞLU KOÇER

Offered to

Data Science
Data Science - (Non-Thesis-Evening)

Course Objective

The aim of this course is to give students a point of view and to give an insight about managing the business processes and making the best decisions in industrial processes. In this course e will focus on how data can be used in matching the supplier and retailer. And also we will focus on the topics about planning both planning the production (or orders) and managing the business processes to serve the customers better quality.

Learning Outcomes of the Course Unit

1   Define the business processes and the relationship between these processes
2   Define the relationship between the supplier and the retailer by using mathematical models
3   Make efficient decisions considering different supplier-retailer designs
4   Implement the inventory models and making decisions
5   Manage the operations in a company in productivity and efficiency point of view

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction and basic concepts: Managing work flow, inventory, thruput, and productivity
2 Workforce planning, line balancing, EOQ model
3 Analytical decision making: Planning with linear programming
4 Case studies about linear programming
5 Effect of randomness in the performance of processes-1: Queueing problems, optimizing the service systems
6 Midterm Exam
7 Effect of randomness in the performance of processes-2: Inventory management under stochastic demand-Newsvendor model
8 Inventory management under stochastic demand--(r,q), (s,S) ve (R,S) policies
9 Case studies about inventory management
10 Inventory management under stochastic demand-Material Requirements Planning
11 Case study about MRP
12 Quality management, control charts and Just-in-Time Production
13 Revenue Management

Recomended or Required Reading

Main textbooks:
1. Matching Supply with Demand. By Gerard Cachon and Christian Terwiesch, McGraw-Hill, 2006.
Supplementary Book(s):
1. Supply Chain Management: Strategy, Planning and Operation. By Sunil Chopra and Peter Meindl. Prentice-Hall, Inc., 2007.

Planned Learning Activities and Teaching Methods

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 ASG ASSIGNMENT
3 PRS 1 PRESENTATION 1
4 PRS 2 PRESENTATION 2
5 FIN FINAL EXAM
6 FCG FINAL COURSE GRADE MTE * 0.20 +ASG * 0.20 + PRS 1 * 0.15 + PRS 2 * 0.15 + FIN * 0.30
7 RST RESIT
8 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.20 +ASG * 0.20 + PRS 1 * 0.15 + PRS 2 * 0.15 + RST * 0.30


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

DEU, Faculty of Science, Department of Statistics
e-mail: umay.uzunoglu@deu.edu.tr
phone: +90 232 301 85 60

Office Hours

Will be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 13 3 39
Preparations before/after weekly lectures 13 3 39
Preparation for midterm exam 1 20 20
Preparation for final exam 1 30 30
Preparing assignments 1 30 30
Preparing presentations 1 30 30
Final 1 3 3
Midterm 1 3 3
TOTAL WORKLOAD (hours) 194

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7
LO.152
LO.2445
LO.34454
LO.454
LO.545