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 mastery of advanced research methodologies (quantitative, qualitative, and mixed methods) by critically analyzing literature, identifying research gaps, and designing original studies that contribute to MIS theory and practice.
- Conduct and defend an original doctoral dissertation that reflects independent scholarly inquiry, academic rigor, and a significant contribution to the advancement of knowledge in MIS.
- Exhibit readiness for thesis monitoring and defense by articulating the philosophical foundations of research paradigms, positioning one's research within these frameworks, and responding to scholarly critique.
- Apply ethical principles, academic integrity, and responsible conduct of research in all phases of the research process, including data collection, analysis, reporting, and publication.
- Identify and address the social, legal, and ethical implications of information systems research and its applications within organizational and societal contexts.
- Employ advanced data science techniques, including statistical modeling, machine learning, and AI-based analytics, to examine complex datasets and extract meaningful insights in MIS research.
- Recognize and evaluate emerging technologies such as artificial intelligence, big data, blockchain, and the Internet of Things, assessing their transformative impact on organizational processes and digital ecosystems.
- Collaborate and lead in interdisciplinary research environments, establishing productive scientific partnerships and managing research projects that integrate diverse academic perspectives.
- Publish high-quality research in peer-reviewed journals, present findings at international conferences, and actively engage in academic service such as journal reviewing, conference organizing, and committee participation.
- Identify challenges and propose innovative, research-based solutions at the intersection of information systems, technology, and organizational strategy.
- Deliver advanced-level MIS courses, supervise graduate research, and nurture academic development through effective mentorship and scholarly teaching.
- Develop advanced information systems and decision support systems that align IT capabilities with organizational strategies using systems thinking and innovative design methodologies.
Po-Lo Matrix
The PO-LO matrix has not been populated yet.