PRODUCTION PLANNING AND SCHEDULING
- Course
- EMNT501 - PRODUCTION PLANNING AND SCHEDULING
- Department
- Engineering Management - English - Master
- Course Type
- Course
- Status
- Required
- Language
- English
- Credit
- 3
- ECTS
- 0
- T+P+L
- 3 + 0 + 0
- Course Coordinator(s)
- Dr. Behzad SANAEI
- Prerequisite
- -
Course Description
The course aims to analysis of some specific problem areas within the context of planning and scheduling of production activities. Also the course give the information related definition, formulation and available solution procedures for aggregate planning and lot sizing. It includes scheduling in manufacturing systems, scheduling in service systems, design and operation of scheduling systems. Students in this course will learn fundamental problem areas of production planning and control and, the relation between planning and control activities. At the end of this course student will be able to define of Production Planning and Control Concepts, decide forecasting and evaluate the forecasting methods, decide lot size of a single item with deterministic and constant demand, compute total cost of an inventory policy and solve lot sizing problems under resource constraint with multiple items.
PRODUCTION PLANNING AND SCHEDULING
Evaluation Tools (Active Term)
| Item | Type | Weight (%) |
|---|---|---|
| Midterm Exam | Midterm | 30 |
| Final Exam | Final | 50 |
| Presentation | Presentation | 20 |
| Total | 100 | |
Course outcomes
- 01 Define of Production Planning and Control Concepts
- 02 Decide forecasting and evaluate the forecasting
- 03 decide aggregate production planning, and master production scheduling, material requirement planing, operational scheduling, Project Planning and CPM.
Course Syllabus
| Week | Topic |
|---|---|
| Week 1 | Introduction to Production Planning and Control |
| Week 2 | Forecasting Fundamentals |
| Week 3 | Quantitative Forecasting Methods |
| Week 4 | Forecasting-Regression Analysis; Time series Methods |
| Week 5 | Introduction to Aggregate Planning; Aspect of Aggregate Planning |
| Week 6 | Spreadsheet Approach to Aggregate Planning; Linear Programming Approaches to Aggregate Planning, Transportation Models |
| Week 7 | Transportation/linear-programming formulation and simple optimization applications |
| Week 8 | Inventory functions and costs; independent demand; EOQ and basic inventory decisions |
| Week 9 | Reorder point, safety stock, service level and basic inventory-control policies |
| Week 10 | Master Production Scheduling and BOM |
| Week 11 | Material Requirements Planning — MRP |
| Week 12 | Capacity Planning and Its Relationship with MPS and MRP |
| Week 13 | Introduction to Operations Scheduling; Scheduling Objectives, Performance Measures, and Basic Priority/Dispatching Rules |
| Week 14 | Single-Machine Sequencing and Simple Scheduling Applications; Johnson's Rule for a Basic Two-Machine Case |
| Week 15 | Project submission and presentations |
Reference Books & Course Materials
- 01 Stevenson, W. J. (2021). Operations Management (14th ed.). McGraw-Hill Education. ISBN: 978-1-260-57571-2.
- 02 Sipper, D., and Bulfin R.L., Production: Planning, Control, and Integration, McGram-Hill,1997, ISBN: 0-07-057682-3.
- 03 Chase, R. B., Jacobs, F. R., & Aquilano, N. J. (2004). Operations Management for Competitive Advantage (10th ed.). McGraw-Hill/Irwin. ISBN: 0-07-250636-9.
- 04 Heizer, J., & Render, B. (1995). Production and Operations Management: Strategic and Tactical Decisions (4th ed.). Prentice Hall. ISBN: 0-13-199423-9.
Learning Outcomes
No learning outcomes have been defined.
Program Outcomes
- Demonstrate advanced knowledge of core concepts and theoretical frameworks in Management Information Systems, and apply them to develop innovative models that reflect current advancements in the field.
- Analyze complex organizational problems and design integrated information systems solutions by applying advanced MIS knowledge and synthesizing multiple theoretical perspectives.
- Develop and manage database systems and data-driven applications that ensure effective storage, retrieval, and use of organizational data in real-world contexts.
- Utilize data analytics, business intelligence tools, and data visualization techniques to extract actionable insights and support strategic, data-driven decision-making.
- Evaluate and apply emerging technologies such as AI, IoT, and Blockchain to drive digital transformation, enhance organizational performance, and formulate original research inquiries.
- Conduct independent and collaborative research using appropriate methodologies, and communicate findings effectively through scholarly writing and presentations suited to diverse audiences.
- dentify and address ethical, legal, and societal implications in the research, development, and use of information technologies, adhering to scientific and professional standards.
- Collaborate effectively in multidisciplinary teams and demonstrate leadership in addressing complex technology-driven challenges.
- Apply project management methodologies and tools to plan, execute, and monitor IT projects within organizational settings.
- Develop and integrate information systems that align with organizational goals and strategies, supporting innovation and sustainable growth.
- Perform comprehensive systems analysis and design, including requirements gathering, modeling, prototyping, and evaluating enterprise system architectures such as ERP, CRM, and SCM.
- Assess and mitigate organizational information security risks by applying appropriate principles, technologies, and best practices in cybersecurity.
Po-Lo Matrix
The PO-LO matrix has not been populated yet.