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SECTION I: GENERAL INFORMATION ABOUT THE COURSE

Course Code Course Name Year Semester Theoretical Practical Credit ECTS
60541MEEOZ-IEN0157 Industrial Engineering Decision Analysis 4 Fall 2 2 3 6
Course Type : Compulsory
Cycle: Bachelor      TQF-HE:6. Master`s Degree      QF-EHEA:First Cycle      EQF-LLL:6. Master`s Degree
Language of Instruction: English
Prerequisities and Co-requisities: 60542TAEOZ-MTH3164 - Probability and Statistics for Engineering
Mode of Delivery: Face to face
Name of Coordinator: Doçent Dr. NEVZAT EVRİM ÖNAL
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SECTION II: INTRODUCTION TO THE COURSE

Course Objectives & Content

Course Objectives: To provide students practical techniques and decision support tools to help them to think clearly about objectives, attributes, alternatives, consequences; enable them to integrate judgments with other types of information in a logical and defensible manner; improve students' decision making skills, their ability to analyze problems systematically, and their confidence in their own decision making.
Course Content: Management Engineering Decision Analysis includes topics such as single person or group decision making under uncertainty and multi-criteria decision making. This course is designed to teach basic decision making tools which are essential for Management Engineering students. This course helps students to improve the quality of the decisions they make in managerial and personal decisions. This course employs the project-based learning approach. In this respect aside from the conventional content the course has a project-based learning component. The project based- learning component aims realising one or more projects designed for learning purposes involving the development of certain intermediary and final deliverables in a step-by-step mannerby the students individually or in project teams. The evaluation of the project-based learning component involves grading the project deliverables and the project works by the instructor and/or a jury.

Course Learning Outcomes (CLOs)

Course Learning Outcomes (CLOs) are those describing the knowledge, skills and competencies that students are expected to achieve upon successful completion of the course. In this context, Course Learning Outcomes defined for this course unit are as follows:
Knowledge (Described as Theoritical and/or Factual Knowledge.)
Skills (Describe as Cognitive and/or Practical Skills.)
  1) Structure and analyze a decision making problem and construct a decision making model.
  2) Choose and implement basic decision making techniques including elementary, value based and outranking methods.
  3) Utilize techniques like analytic hierarchy process, analytic network process and artificial neural networks.
  4) Choose and implement basic group decision making techniques in different circumstances.
Competences (Described as "Ability of the learner to apply knowledge and skills autonomously with responsibility", "Learning to learn"," Communication and social" and "Field specific" competences.)

Weekly Course Schedule

Week Subject
Materials Sharing *
Related Preparation Further Study
1) Introduction to Decision Making, Structuring the Problem Reading assignment, Preparatory study Project work, Homework assignment
2) Assignment of projects Reading assignment, Preparatory study Project work, Homework assignment
3) Constructing the Decision Model, Analyzing the Problem Reading assignment, Preparatory study Project work, Homework assignment
4) Cognitive Mapping, Bayesian Belief Networks Reading assignment, Preparatory study Project work, Homework assignment
5) The Analytic Hierarchy Process Reading assignment, Preparatory study Project work, Homework assignment
6) The Analytic Network Process, Elementary Methods Reading assignment, Preparatory study Project work, Homework assignment
7) Submission of the first delivery of the project Reading assignment, Preparatory study Project work, Homework assignment
8) Midterm Exam Reading assignment, Preparatory study Project work, Homework assignment
9) Value Based Methods Reading assignment, Preparatory study Project work, Homework assignment
10) Outranking Methods Reading assignment, Preparatory study Project work, Homework assignment
11) Decision Making under Uncertainty & under Risk, Utility Theory, Decision Trees Reading assignment, Preparatory study Project work, Homework assignment
12) Submission of the first delivery of the project Reading assignment, Preparatory study Project work, Homework assignment
13) Artificial Neural Networks Reading assignment, Preparatory study Project work, Homework assignment
14) Group Decision Making Reading assignment, Preparatory study Project work, Homework assignment
15) Submission of the final delivery of the project and presentation Reading assignment, Preparatory study Project work, Homework assignment
*These fields provides students with course materials for their pre- and further study before and after the course delivered.

Recommended or Required Reading & Other Learning Resources/Tools

Course Notes / Textbooks: Bazerman, M.H. 2002. Judgment in Managerial Decision Making. 5th Ed., John Wiley & Sons, New York.
References: Jeffrey W. Herrmann, Engineering Decision Making and Risk Management, ISBN-13: 978-1118919330

Patricia Guarnieri, Decision Models in Engineering and Management, ISBN: 978-3-319-11948-9

John C. Hsu, 2019, Decision Analysis and Interface Management in Systems Engineering

David C Skinner, Introduction to Decision Analysis, Third Edition, ISBN: 978-0964793866


SECTION III: RELATIONSHIP BETWEEN COURSE UNIT AND COURSE LEARNING OUTCOMES (CLOs)

(The matrix below shows how the course learning outcomes (CLOs) associates with programme learning outcomes (both KPLOs & SPLOs) and, if exist, the level of quantitative contribution to them.)

Relationship Between CLOs & PLOs

(KPLOs and SPLOs are the abbreviations for Key & Sub- Programme Learning Outcomes, respectively. )
CLOs/PLOs KPLO 1 KPLO 2 KPLO 3 KPLO 4 KPLO 5
1 1 2 3 4 5 1 2 3 4 5 6 7 8 9 1 2 3 4 1 2 3 4 5 6 7 8 9 10 11 12
CLO1
CLO2
CLO3
CLO4

Level of Contribution of the Course to PLOs

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
           
Programme Learning Outcomes Contribution Level (from 1 to 5)
1) Uses and applies theoretical and applied sciences in the field of basic science subjects for the solution of industrial engineering problems. 3
2) Analyzes Industrial Engineering applications, designs and develops models to meet specific requirements under realistic constraints and conditions. For this purpose, it selects and uses appropriate methods, tools and technologies. 5
3) Owns the competencies required by the constantly developing field of industrial engineering and the global competitive environment. 1
4) Applies the theoretical knowledge in business life during a semester.
5) S/he acquires the competencies that develop by the expectations of business world and the society defined as the institutional outcomes of our university on the advanced level in relation with his/her field.

SECTION IV: TEACHING-LEARNING & ASSESMENT-EVALUATION METHODS OF THE COURSE

Teaching & Learning Methods of the Course

(All teaching and learning methods used at the university are managed systematically. Upon proposals of the programme units, they are assessed by the relevant academic boards and, if found appropriate, they are included among the university list. Programmes, then, choose the appropriate methods in line with their programme design from this list. Likewise, appropriate methods to be used for the course units can be chosen among those defined for the programme.)
Teaching and Learning Methods defined at the Programme Level
Teaching and Learning Methods Defined for the Course
Lectures
Discussion
Case Study
Problem Solving
Demonstration
Views
Laboratory
Reading
Homework
Project Preparation
Thesis Preparation
Peer Education
Seminar
Technical Visit
Course Conference
Brain Storming
Questions Answers
Individual and Group Work
Role Playing-Animation-Improvisation
Active Participation in Class

Assessment & Evaluation Methods of the Course

(All assessment and evaluation methods used at the university are managed systematically. Upon proposals of the programme units, they are assessed by the relevant academic boards and, if found appropriate, they are included among the university list. Programmes, then, choose the appropriate methods in line with their programme design from this list. Likewise, appropriate methods to be used for the course units can be chosen among those defined for the programme.)
Aassessment and evaluation Methods defined at the Programme Level
Assessment and Evaluation Methods defined for the Course
Midterm
Presentation
Final Exam
Quiz
Report Evaluation
Homework Evaluation
Oral Exam
Thesis Defense
Jury Evaluation
Practice Exam
Evaluation of Implementation Training in the Workplace
Active Participation in Class
Participation in Discussions

Relationship Between CLOs & Teaching-Learning, Assesment-Evaluation Methods of the Course

(The matrix below shows the teaching-learning and assessment-evaluation methods designated for the course unit in relation to the course learning outcomes.)
LEARNING & TEACHING METHODS
COURSE LEARNING OUTCOMES
ASSESMENT & EVALUATION METHODS
CLO1 CLO2 CLO3 CLO4
-Lectures -Midterm
-Discussion -Presentation
-Case Study -Final Exam
-Problem Solving -Quiz
-Demonstration -Report Evaluation
-Views -Homework Evaluation
-Laboratory -Oral Exam
-Reading -Thesis Defense
-Homework -Jury Evaluation
-Project Preparation -Practice Exam
-Thesis Preparation -Evaluation of Implementation Training in the Workplace
-Peer Education -Active Participation in Class
-Seminar - Participation in Discussions
-Technical Visit
-Course Conference
-Brain Storming
-Questions Answers
-Individual and Group Work
-Role Playing-Animation-Improvisation
-Active Participation in Class

Contribution of Assesment & Evalution Activities to Final Grade of the Course

Measurement and Evaluation Methods # of practice per semester Level of Contribution
Total %
PERCENTAGE OF SEMESTER WORK % 0
PERCENTAGE OF FINAL WORK %
Total %

SECTION V: WORKLOAD & ECTS CREDITS ALLOCATED FOR THE COURSE

WORKLOAD OF TEACHING & LEARNING ACTIVITIES
Teaching & Learning Activities # of Activities per semester Duration (hour) Total Workload
Course 14 2 28
Laboratory 0 0 0
Application 14 2 28
Special Course Internship (Work Placement) 0 0 0
Field Work 0 0 0
Study Hours Out of Class 14 2 28
Presentations / Seminar 4 1 4
Project 4 10 40
Homework Assignments 0 0 0
Total Workload of Teaching & Learning Activities - - 128
WORKLOAD OF ASSESMENT & EVALUATION ACTIVITIES
Assesment & Evaluation Activities # of Activities per semester Duration (hour) Total Workload
Quizzes 3 2 6
Midterms 1 6 6
Semester Final Exam 1 12 12
Total Workload of Assesment & Evaluation Activities - - 24
TOTAL WORKLOAD (Teaching & Learning + Assesment & Evaluation Activities) 152
ECTS CREDITS OF THE COURSE (Total Workload/25.5 h) 6