Industrial Engineering
Course Details
KTO KARATAY UNIVERSITY
Mühendislik ve Doğa Bilimleri Fakültesi
Programme of Industrial Engineering
Course Details
Mühendislik ve Doğa Bilimleri Fakültesi
Programme of Industrial Engineering
Course Details
| Course Code | Course Name | Year | Period | Semester | T+A+L | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| 15271722 | Sequencing and Scheduling | 4 | Autumn | 7 | 3+0+0 | 0 | 5 |
| Course Type | Elective |
| Course Cycle | Bachelor's (First Cycle) (TQF-HE: Level 6 / QF-EHEA: Level 1 / EQF-LLL: Level 6) |
| Course Language | Turkish |
| Methods and Techniques | - |
| Mode of Delivery | Face to Face |
| Prerequisites | - |
| Coordinator | Prof. Murat DARÇIN |
| Instructor(s) | Asst. Prof. Esra BOZ |
| Instructor Assistant(s) | - |
Course Content
Bir makine üretim tipleri, paralel makineleri, iş salonu üretim, açık iş salonu üretim, kurmak ve zamanlama, zamanlama ve optimizasyon heuristics hazırlama süresi: G-wright, Genetik algoritma, karınca kolonisi ve tabu arama
Objectives of the Course
In an manufacturing system to teach the scheduling of processes according to constraints, machines types and capacities.
Contribution of the Course to Field Teaching
| Basic Vocational Courses | |
| Specialization / Field Courses | X |
| Support Courses | |
| Transferable Skills Courses | |
| Humanities, Communication and Management Skills Courses |
Relationships between Course Learning Outcomes and Program Outcomes
| Relationship Levels | ||||
| Lowest | Low | Medium | High | Highest |
| 1 | 2 | 3 | 4 | 5 |
| # | Program Learning Outcomes | Level |
|---|---|---|
| P2 | Ability to identify, formulate and solve complex Industrial Engineering problems; Ability to select and apply appropriate analysis and modeling methods for this purpose | 5 |
Course Learning Outcomes
| Upon the successful completion of this course, students will be able to: | |||
|---|---|---|---|
| No | Learning Outcomes | Outcome Relationship | Measurement Method ** |
| O1 | Farklı sıralama algoritmalarını tanımlayıp, uygulama becerisi kazanır. | P.2.109 | 1 |
| O2 | Çizelgeleme problemlerini analiz ederek, optimal çözümler geliştirir. | P.2.110 | 1 |
| O3 | İş süreçlerini optimize etmek için sıralama ve çizelgeleme tekniklerini uygular. | P.2.111 | 1 |
| O4 | Gerçek dünya senaryolarında sıralama ve çizelgeleme çözümlerini değerlendirme yeteneği kazanır. | P.2.112 | 1 |
| ** Written Exam: 1, Oral Exam: 2, Homework: 3, Lab./Exam: 4, Seminar/Presentation: 5, Term Paper: 6, Application: 7 | |||
Weekly Detailed Course Contents
| Week | Topics |
|---|---|
| 1 | Production and production planning |
| 2 | Symbols used in scheduling |
| 3 | SPT, LPT and EDD rules |
| 4 | Lawler algorithm |
| 5 | Moore Algorithm |
| 6 | Moore Algorithm |
| 7 | M-Johnson Algorithm |
| 8 | Ara sınav |
| 9 | M-Johnson Algorithm |
| 10 | Dynamic programming |
| 11 | Dynamic programming |
| 12 | Branch&Bound |
| 13 | Branch&Bound |
| 14 | Branch&Bound |
| 15 | G-wright heuristic algorithm |
Textbook or Material
| Resources | İmalat Sistemlerinde Çizelgeleme Atama – Sıralama – Zamanlama, Seçkin Yayıncılık, 2022 |
Evaluation Method and Passing Criteria
| In-Term Studies | Quantity | Percentage |
|---|---|---|
| Attendance | - | - |
| Laboratory | - | - |
| Practice | - | - |
| Field Study | - | - |
| Course Specific Internship (If Any) | - | - |
| Homework | - | - |
| Presentation | - | - |
| Projects | - | - |
| Seminar | - | - |
| Quiz | - | - |
| Listening | - | - |
| Midterms | 1 | 40 (%) |
| Final Exam | 1 | 60 (%) |
| Total | 100 (%) | |
ECTS / Working Load Table
| Quantity | Duration | Total Work Load | |
|---|---|---|---|
| Course Week Number and Time | 14 | 3 | 42 |
| Out-of-Class Study Time (Pre-study, Library, Reinforcement) | 14 | 3 | 42 |
| Midterms | 1 | 30 | 30 |
| Quiz | 0 | 0 | 0 |
| Homework | 0 | 0 | 0 |
| Practice | 0 | 0 | 0 |
| Laboratory | 0 | 0 | 0 |
| Project | 0 | 0 | 0 |
| Workshop | 0 | 0 | 0 |
| Presentation/Seminar Preparation | 0 | 0 | 0 |
| Fieldwork | 0 | 0 | 0 |
| Final Exam | 1 | 36 | 36 |
| Other | 0 | 0 | 0 |
| Total Work Load: | 150 | ||
| Total Work Load / 30 | 5 | ||
| Course ECTS Credits: | 5 | ||
Course - Learning Outcomes Matrix
| Relationship Levels | ||||
| Lowest | Low | Medium | High | Highest |
| 1 | 2 | 3 | 4 | 5 |
| # | Learning Outcomes | P2 |
|---|---|---|
| O1 | Farklı sıralama algoritmalarını tanımlayıp, uygulama becerisi kazanır. | 5 |
| O2 | Çizelgeleme problemlerini analiz ederek, optimal çözümler geliştirir. | 5 |
| O3 | İş süreçlerini optimize etmek için sıralama ve çizelgeleme tekniklerini uygular. | 5 |
| O4 | Gerçek dünya senaryolarında sıralama ve çizelgeleme çözümlerini değerlendirme yeteneği kazanır. | 5 |