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Fees
₹8,50,000
Placement
94.5%
Avg Package
₹8,50,000
Highest Package
₹18,00,000
Fees
₹8,50,000
Placement
94.5%
Avg Package
₹8,50,000
Highest Package
₹18,00,000
Seats
120
Students
120
Seats
120
Students
120
The Supply Chain Management curriculum at RKDF INSTITUTE OF MANAGEMENT is meticulously structured to provide students with a comprehensive foundation in both theoretical and applied aspects of the field. The program spans eight semesters, integrating core engineering principles with business strategy and advanced analytics.
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | PHYS101 | Physics for Engineering | 3-1-0-4 | - |
| 1 | MATH101 | Calculus and Linear Algebra | 3-1-0-4 | - |
| 1 | CHEM101 | Chemistry for Engineers | 2-1-0-3 | - |
| 1 | ENG101 | English Communication Skills | 2-0-0-2 | - |
| 1 | CS101 | Introduction to Computer Science | 3-1-0-4 | - |
| 1 | ELEC101 | Basic Electrical Engineering | 3-1-0-4 | - |
| 2 | MATH201 | Differential Equations and Numerical Methods | 3-1-0-4 | MATH101 |
| 2 | CIVL201 | Engineering Mechanics | 3-1-0-4 | - |
| 2 | MECH201 | Thermodynamics and Heat Transfer | 3-1-0-4 | - |
| 2 | COMP201 | Data Structures and Algorithms | 3-1-0-4 | CS101 |
| 2 | STAT201 | Probability and Statistics | 3-1-0-4 | MATH101 |
| 2 | ECON201 | Introduction to Economics | 3-1-0-4 | - |
| 3 | MECH301 | Mechanical Systems and Dynamics | 3-1-0-4 | MECH201 |
| 3 | COMP301 | Database Management Systems | 3-1-0-4 | COMP201 |
| 3 | MATH301 | Operations Research | 3-1-0-4 | MATH201 |
| 3 | BUSI301 | Introduction to Business Management | 3-1-0-4 | - |
| 3 | STAT301 | Statistical Inference and Regression Analysis | 3-1-0-4 | STAT201 |
| 3 | ENGR301 | Engineering Design and Innovation | 3-1-0-4 | - |
| 4 | MATH401 | Advanced Linear Programming | 3-1-0-4 | MATH301 |
| 4 | COMP401 | Software Engineering Principles | 3-1-0-4 | COMP301 |
| 4 | BUSI401 | Strategic Management | 3-1-0-4 | BUSI301 |
| 4 | LOGI401 | Introduction to Logistics and Supply Chain | 3-1-0-4 | - |
| 4 | ECON401 | International Trade Theory | 3-1-0-4 | ECON201 |
| 4 | STAT401 | Time Series Analysis and Forecasting | 3-1-0-4 | STAT301 |
| 5 | LOGI501 | Supply Chain Modeling and Simulation | 3-1-0-4 | LOGI401 |
| 5 | MATH501 | Decision Making Under Uncertainty | 3-1-0-4 | MATH401 |
| 5 | BUSI501 | Operations Management | 3-1-0-4 | BUSI401 |
| 5 | COMP501 | Machine Learning for Business Applications | 3-1-0-4 | COMP401 |
| 5 | ECON501 | Global Economic Environment | 3-1-0-4 | ECON401 |
| 5 | ENGR501 | Industrial Engineering Fundamentals | 3-1-0-4 | ENGR301 |
| 6 | LOGI601 | Digital Transformation in Supply Chains | 3-1-0-4 | LOGI501 |
| 6 | BUSI601 | Strategic Sourcing and Supplier Management | 3-1-0-4 | BUSI501 |
| 6 | COMP601 | Big Data Analytics for SCM | 3-1-0-4 | COMP501 |
| 6 | MATH601 | Optimization Techniques in Logistics | 3-1-0-4 | MATH501 |
| 6 | ECON601 | Trade Policy and Commercial Law | 3-1-0-4 | ECON501 |
| 6 | ENGR601 | Supply Chain Risk Management | 3-1-0-4 | ENGR501 |
| 7 | LOGI701 | Sustainable Supply Chain Practices | 3-1-0-4 | LOGI601 |
| 7 | BUSI701 | Enterprise Resource Planning Systems | 3-1-0-4 | BUSI601 |
| 7 | COMP701 | Blockchain Applications in Logistics | 3-1-0-4 | COMP601 |
| 7 | MATH701 | Advanced Predictive Analytics | 3-1-0-4 | MATH601 |
| 7 | ECON701 | Regional Development and Infrastructure | 3-1-0-4 | ECON601 |
| 7 | ENGR701 | Logistics Network Design | 3-1-0-4 | ENGR601 |
| 8 | LOGI801 | Capstone Project in Supply Chain Management | 3-1-0-4 | LOGI701 |
| 8 | BUSI801 | Strategic Leadership in SCM | 3-1-0-4 | BUSI701 |
| 8 | COMP801 | Final Project Presentation and Documentation | 3-1-0-4 | COMP701 |
| 8 | MATH801 | Research Methodology in SCM | 3-1-0-4 | MATH701 |
| 8 | ECON801 | Economic Impact of Supply Chain Disruptions | 3-1-0-4 | ECON701 |
| 8 | ENGR801 | Industrial Internship and Professional Development | 3-1-0-4 | ENGR701 |
Each course in the curriculum is designed to build upon previous knowledge while introducing new methodologies and tools essential for modern supply chain professionals. The structure ensures a balance between technical depth and business relevance, preparing students for diverse roles across industries.
Students are exposed to advanced elective courses in their third and fourth years that further specialize their knowledge:
This course equips students with the skills to forecast demand, optimize inventory levels, and predict disruptions using statistical and machine learning models. Students will use real-world datasets from major logistics providers like DHL and UPS to build predictive algorithms.
Focused on identifying potential risks in global supply chains, this course teaches students how to evaluate vulnerabilities and implement mitigation strategies. Topics include geopolitical risks, natural disasters, cyber threats, and supplier dependency issues.
Students explore the transformative impact of blockchain technology on transparency, traceability, and security in supply chains. The course includes hands-on lab sessions where students develop decentralized applications for tracking goods from origin to destination.
This elective introduces students to tools like Hadoop, Spark, and Kafka used in processing large volumes of logistics data. Students will perform analytics on live datasets to optimize routing, reduce costs, and improve delivery times.
With the rapid growth of online retail, this course covers specialized topics such as reverse logistics, customer experience optimization, and innovative delivery models like drone delivery and micro-fulfillment centers.
This course explores sustainable practices in supply chains, including carbon footprint reduction, green procurement, and circular economy principles. Students will analyze case studies from companies committed to environmental responsibility.
Students learn how to select suppliers globally, negotiate contracts, manage supplier performance, and maintain long-term relationships. The course includes visits to manufacturing plants and procurement offices of leading firms.
This course delves into the mathematical and operational aspects of designing efficient transportation networks. Students will model different transportation modes and optimize routes using software like ArcGIS and MATLAB.
Students explore how digital twin technology can simulate real-world logistics operations, enabling predictive maintenance, capacity planning, and scenario modeling for complex supply chains.
This course covers international trade regulations, customs procedures, and compliance frameworks. Students will analyze tariff structures, export controls, and documentation requirements for global commerce.
The department strongly believes in experiential learning as a catalyst for deep understanding and innovation. The program emphasizes project-based learning through mandatory mini-projects and a capstone thesis that aligns with real-world challenges.
Mini-projects are undertaken during the second and third years, focusing on specific themes such as warehouse layout optimization or demand forecasting using historical data. These projects require students to work in teams, collaborate with faculty mentors, and present findings to industry experts.
The final-year capstone project allows students to choose a topic aligned with their interests and career goals. Projects are often sponsored by industry partners, providing students with direct exposure to business challenges and opportunities for collaboration.
Evaluation criteria include technical depth, innovation, presentation quality, and impact potential. Faculty mentors guide students throughout the process, ensuring that projects meet academic standards while remaining relevant to current industry trends.
