ECTS - Production Planning and Control
Production Planning and Control (IE307) Course Detail
| Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| Production Planning and Control | IE307 | 5. Semester | 3 | 0 | 0 | 3 | 5 |
| Pre-requisite Course(s) |
|---|
| N/A |
| Course Language | English |
|---|---|
| Course Type | Compulsory Departmental Courses |
| Course Level | Bachelor’s Degree (First Cycle) |
| Mode of Delivery | Face To Face |
| Learning and Teaching Strategies | Lecture, Discussion, Question and Answer, Problem Solving. |
| Course Lecturer(s) |
|
| Course Objectives | This course is designed to develop a basic understanding of major production planning concerns and decision chains, fundamental problem areas in production planning and control, planning hierarchy and the relations with the management activities. |
| Course Learning Outcomes |
The students who succeeded in this course;
|
| Course Content | Introduction to production and service systems; forecasting methods; production planning and control in decision making; aggregate production planning; capacity planning; materials requirement planning; scheduling; advanced techniques and approaches in modern production planning and control for designing manufacturing and service systems. |
Weekly Subjects and Releated Preparation Studies
| Week | Subjects | Preparation |
|---|---|---|
| 1 | Introduction to Production and Service Systems, Basic Concepts of Planning (Planning Horizons, Production Type and Classifications, Product-Process Life Cycles, Learning and Experience curves, Economies of Scale/Scope) | Nahmias and Olsen: Chapter 1, pp. 27-38 |
| 2 | Forecasting (Qualitative and Quantitative methods, Importance of Forecasting for the Planning Hierarchy) | Nahmias and Olsen: Chapter 2, pp. 55-75 |
| 3 | Forecasting (Qualitative and Quantitative Methods, Importance of Forecasting for the Planning Hierarchy) | Nahmias and Olsen: Chapter 2, pp. 77-80 |
| 4 | Forecasting (Qualitative and Quantitative Methods, Importance of Forecasting for the Planning Hierarchy) | Nahmias and Olsen: Chapter 2, pp. 81-90 |
| 5 | Definitions of Production Planning and Inventory Management Concepts, Economic Order Quantity (EOQ) Policy and Extensions | Nahmias and Olsen: Chapter 4, pp. 201-217 |
| 6 | Economic Production Quantity Policy (EPQ) Policy | Nahmias and Olsen: Chapter 4, pp. 218-220 |
| 7 | Economic Lot-Scheduling Problem for Multiple Products Sharing the Same Capacity | Nahmias and Olsen: Chapter 4, pp. 228-236 |
| 8 | A-B-C Product Classification, Inventory Replenishment Policies in case of Stochastic Demand and Importance of Safety Stock, Midterm Exam | Silver, Pyke, and Peterson: Chapter 7, pp. 232-244 |
| 9 | Stockout Cost Measures and Continuous-Review Reorder Point Policy | Silver, Pyke, and Peterson: Chapter 7, pp. 247-252 |
| 10 | Stockout Cost Measures and Continuous-Review Reorder Point Policy | Silver, Pyke, and Peterson: Chapter 7, pp. 253-265 |
| 11 | Master Production Scheduling (MPS) and Material Requirements Planning (MRP) (Basic MRP Definitions and Mechanics: Rolling Horizons and Bill-Of-Materials Explosion) | Nahmias and Olsen: Chapter 8, pp. 437-449 |
| 12 | Material Requirements Planning (MRP) (Lot-Sizing Rules for the Determination of Replenishment Order Sizes and Capacity Planning) | Nahmias and Olsen: Chapter 8, pp. 449-457, 462-467 |
| 13 | Shortcomings of Material Requirements Planning (MRP), The Fundamentals of Just-In-time (JIT) Approach and Lean Production | Nahmias and Olsen: Chapter 8, pp. 461-478 |
| 14 | Job Shop Scheduling (Single-Machine Sequencing Rules) | Nahmias and Olsen: Chapter 9, pp. 490-509 |
| 15 | Job Shop Scheduling (Scheduling on Multiple Machines: Johnson’s Algorithm) | Nahmias and Olsen: Chapter 9, pp. 510-518 |
| 16 | Final Exam |
Sources
| Course Book | 1. Nahmias, S., and Olsen, T.L. (2015), Production and Operations Analysis, 7th Edition, McGraw-Hill. |
|---|---|
| Other Sources | 2. Silver, E.A., Pyke, D.F., and Peterson, R. (1998), Inventory Management and Production Planning and Scheduling, 3rd Edition, John Wiley & Sons. |
| 3. Buffa, E.S., and Sarin, R.K. (1987), Modern Production/Operations Management, John Wiley. | |
| 4. Johnson, L.A., and Montgomery, D.C. (1974), Operations Research in Production Planning, Scheduling, and Inventory Control, John Wiley. | |
| 5. Sipper, D., and Bulfin, R.L. (1997), Production: Planning, Control, and Integration, McGraw Hill. |
Evaluation System
| Requirements | Number | Percentage of Grade |
|---|---|---|
| Attendance/Participation | 1 | 10 |
| Laboratory | - | - |
| Application | - | - |
| Field Work | - | - |
| Special Course Internship | - | - |
| Quizzes/Studio Critics | 5 | 20 |
| Homework Assignments | - | - |
| Presentation | - | - |
| Project | - | - |
| Report | - | - |
| Seminar | - | - |
| Midterms Exams/Midterms Jury | 1 | 30 |
| Final Exam/Final Jury | 1 | 40 |
| Toplam | 8 | 100 |
| Percentage of Semester Work | 60 |
|---|---|
| Percentage of Final Work | 40 |
| 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 | Gains adequate knowledge in mathematics, science, and relevant engineering disciplines and acquires the ability to use theoretical and applied knowledge in these fields to solve complex engineering problems. | X | ||||
| 2 | Gains the ability to identify, formulate, and solve complex engineering problems and the ability to select and apply appropriate analysis and modeling methods for this purpose. | X | ||||
| 3 | Gains the ability to design a complex system, process, device, or product under realistic constraints and conditions to meet specific requirements and to apply modern design methods for this purpose. | |||||
| 4 | Gains the ability to select and use modern techniques and tools necessary for the analysis and solution of complex engineering problems encountered in industrial engineering applications and the ability to use information technologies effectively. | X | ||||
| 5 | Gains the ability to design experiments, conduct experiments, collect data, analyze results, and interpret findings for investigating complex engineering problems or discipline specific research questions. | |||||
| 6 | Gains the ability to work effectively in intra-disciplinary and multi-disciplinary teams and the ability to work individually. | |||||
| 7 | Gains the ability to communicate effectively in written and oral form, acquires proficiency in at least one foreign language, the ability to write effective reports and understand written reports, prepare design and production reports, make effective presentations, and give and receive clear and intelligible instructions. | |||||
| 8 | Gains awareness of the need for lifelong learning and the ability to access information, follow developments in science and technology, and to continue to educate him/herself. | |||||
| 9 | Gains knowledge about behaviour in accordance with ethical principles, professional and ethical responsibility and standards used in industrial engineering applications | |||||
| 10 | Gains knowledge about business practices such as project management, risk management, and change management and develops awareness of entrepreneurship, innovation, and sustainable development. | |||||
| 11 | Gains knowledge about the global and social effects of industrial engineering practices on health, environment, and safety, and contemporary issues of the century reflected into the field of engineering; awareness of the legal consequences of engineering solutions. | |||||
| 12 | Gains skills in the design, development, implementation, and improvement of integrated systems involving human, material, information, equipment, and energy. | X | ||||
| 13 | Gains knowledge about appropriate analytical and experimental methods, as well as computational methods, for ensuring system integration. | X | ||||
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 | 4 | 64 |
| Presentation/Seminar Prepration | |||
| Project | |||
| Report | |||
| Homework Assignments | |||
| Quizzes/Studio Critics | 5 | 1 | 5 |
| Prepration of Midterm Exams/Midterm Jury | 1 | 4 | 4 |
| Prepration of Final Exams/Final Jury | 1 | 4 | 4 |
| Total Workload | 125 | ||