Scheduling (IE434) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Scheduling IE434 Area Elective 3 0 0 3 5
Pre-requisite Course(s)
N/A
Course Language English
Course Type Elective Courses
Course Level Natural & Applied Sciences Master's Degree
Mode of Delivery Face To Face
Learning and Teaching Strategies Lecture, Discussion, Question and Answer, Problem Solving.
Course Coordinator
Course Lecturer(s)
Course Assistants
Course Objectives Upon successful completion of this course, the student will be able to conceptualize the overall scheduling process, its prerequisites, its integration with computer systems and other production management systems especially in shop scheduling and have both the analytical thinking skills and practical tools to solve related scheduling problems.
Course Learning Outcomes The students who succeeded in this course;
  • Students will be able to clearly define what is scheduling activity and its importance, and to demonstrate the top-down relation of different levels of scheduling.
  • Students will be able to define the performance criteria/criterion for a schedule and devise measures for evaluation.
  • Students will be able to define and identify problems and their solution techniques/tools for effective master and job shop scheduling process in real life situations.
  • Students will be able to develop practical models that will improve shop level scheduling process.
Course Content Scheduling and sequencing problems, basic formulation, single processor, multi processor scheduling procedures and heuristics.

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 Introduction to and levels of Scheduling tasks in a manufacturing company
2 Prerequisites for effective scheduling activity and contribution of key topics to scheduling process.
3 Prerequisites for effective scheduling activity and contribution of key topics to scheduling process.
4 Master Scheduling and detail Parts Flow - Work Center Scheduling
5 Master Scheduling and detail Parts Flow - Work Center Scheduling
6 Master Scheduling and detail Parts Flow - Work Center Scheduling
7 Master Scheduling and detail Parts Flow - Work Center Scheduling
8 Master Scheduling and detail Parts Flow - Work Center Scheduling
9 Master Scheduling and detail Parts Flow - Work Center Scheduling
10 Master Scheduling and detail Parts Flow - Work Center Scheduling
11 Master Scheduling and detail Parts Flow - Work Center Scheduling
12 Midterm
13 A Practical Machine Loading Method for small or medium size companies
14 Presentations and discussions on term projects.
15 Review and evaluation of the topics covered within the course.
16 Final Exam

Sources

Course Book 1. Michael L. Pinedo, Scheduling Theory, Algorithms, and Systems (5th edition), Springer, 2016
Other Sources 2. Nahmias, S., Production and Operations Analysis, 5th edition, Irwin McGraw-Hill, 2005.
4. Mike Rother and John Shook, Learning to See: Value Stream Mapping to add value and eliminate muda, version 1.1, The Lean Enterprise Institute, 1998.
5. Michael L. Pinedo, Planning and Scheduling in Manufacturing and Services (2nd edition) Springer, 2009
6. J. Thomas Shields, The Lean Aircraft Initiative Report Series #RP96-06-61: Factory Flow Benchmarking Report, Massachusetts Institute of Technology, 1996.

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation - -
Laboratory - -
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics - -
Homework Assignments 2 10
Presentation 1 25
Project - -
Report - -
Seminar - -
Midterms Exams/Midterms Jury 1 30
Final Exam/Final Jury 1 35
Toplam 5 100
Percentage of Semester Work 65
Percentage of Final Work 35
Total 100

Course Category

Core Courses X
Major Area Courses
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

The Relation Between Course Learning Competencies and Program Qualifications

# Program Qualifications / Competencies Level of Contribution
1 2 3 4 5
1 Ability to apply the acquired knowledge in mathematics, science and engineering
2 Ability to identify, formulate and solve complex engineering problems X
3 Ability to accomplish the integration of systems
4 Ability to design, develop, implement and improve complex systems, components, or processes
5 Ability to select/develop and use suitable modern engineering techniques and tools X
6 Ability to design/conduct experiments and collect/analyze/interpret data X
7 Ability to function independently and in teams X
8 Ability to make use of oral and written communication skills effectively
9 Ability to recognize the need for and engage in life-long learning
10 Ability to understand and exercise professional and ethical responsibility
11 Ability to understand the impact of engineering solutions
12 Ability to have knowledge of contemporary issues

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours) 16 3 48
Laboratory
Application
Special Course Internship
Field Work
Study Hours Out of Class 16 2 32
Presentation/Seminar Prepration
Project 1 20 20
Report
Homework Assignments 2 5 10
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury 1 5 5
Prepration of Final Exams/Final Jury 1 10 10
Total Workload 125