Course Structure Overview

The Supply Chain Management program at MAHARISHI CENTRE FOR EDUCATIONAL EXCELLENCE is structured over 8 semesters, with each semester containing a mix of core courses, departmental electives, science electives, and laboratory sessions. The curriculum is designed to provide students with both theoretical knowledge and practical application through experiential learning.

Semester	Course Code	Course Title	Credit Structure (L-T-P-C)	Prerequisites
I	ENG101	English for Communication	3-0-0-3	None
I	MAT101	Calculus I	4-0-0-4	None
I	PHY101	Physics for Engineers	3-0-0-3	None
I	CHE101	Chemistry	3-0-0-3	None
I	CS101	Introduction to Programming	2-0-2-4	None
I	BMS101	Business Management Fundamentals	3-0-0-3	None
I	LAB101	Programming Lab	0-0-2-2	CS101
II	MAT102	Calculus II	4-0-0-4	MAT101
II	ENG102	Technical Writing	3-0-0-3	ENG101
II	MECH101	Engineering Mechanics	3-0-0-3	PHY101
II	ELEC101	Basic Electrical Circuits	3-0-0-3	None
II	CS102	Data Structures and Algorithms	3-0-0-3	CS101
II	BMS102	Introduction to Operations Management	3-0-0-3	None
II	LAB102	Data Structures Lab	0-0-2-2	CS102
III	MAT201	Linear Algebra	3-0-0-3	MAT102
III	STAT101	Probability and Statistics	3-0-0-3	MAT102
III	MECH102	Thermodynamics	3-0-0-3	MECH101
III	ELEC102	Electronics	3-0-0-3	ELEC101
III	CS201	Database Management Systems	3-0-0-3	CS102
III	SCM101	Introduction to Supply Chain Management	3-0-0-3	BMS102
III	LAB201	Database Lab	0-0-2-2	CS201
IV	MAT202	Differential Equations	3-0-0-3	MAT201
IV	STAT201	Applied Statistics	3-0-0-3	STAT101
IV	MECH201	Mechanics of Materials	3-0-0-3	MECH102
IV	ELEC201	Signals and Systems	3-0-0-3	ELEC102
IV	CS202	Computer Architecture	3-0-0-3	CS201
IV	SCM201	Supply Chain Logistics	3-0-0-3	SCM101
IV	LAB202	Computer Architecture Lab	0-0-2-2	CS202
V	MAT301	Numerical Methods	3-0-0-3	MAT202
V	STAT301	Regression Analysis	3-0-0-3	STAT201
V	SCM301	Inventory Management	3-0-0-3	SCM201
V	SCM302	Transportation Systems	3-0-0-3	SCM201
V	SCM303	Risk Assessment in Supply Chains	3-0-0-3	SCM201
V	CS301	Machine Learning Fundamentals	3-0-0-3	CS202
V	LAB301	Mini Project Lab	0-0-4-4	None
VI	MAT302	Optimization Techniques	3-0-0-3	MAT301
VI	SCM401	Demand Forecasting	3-0-0-3	SCM301
VI	SCM402	Supplier Relationship Management	3-0-0-3	SCM302
VI	SCM403	Sustainable Supply Chain Practices	3-0-0-3	SCM301
VI	CS401	Advanced Data Analytics	3-0-0-3	CS301
VI	LAB401	Analytics Lab	0-0-2-2	CS401
VII	SCM501	Supply Chain Innovation and Digital Transformation	3-0-0-3	SCM401
VII	SCM502	Global Supply Chain Strategy	3-0-0-3	SCM402
VII	SCM503	Blockchain Applications in Logistics	3-0-0-3	SCM403
VII	CS501	Cloud Computing for Supply Chains	3-0-0-3	CS401
VII	LAB501	Capstone Project Lab	0-0-6-6	None
VIII	SCM601	Advanced Supply Chain Research	3-0-0-3	SCM501
VIII	SCM602	Internship	0-0-0-10	None
VIII	SCM603	Final Year Thesis	0-0-0-12	SCM601

Advanced Departmental Electives

The department offers several advanced elective courses designed to deepen students' understanding of specialized areas within supply chain management. These courses are taught by leading faculty members and incorporate real-world case studies, industry data, and research-driven insights.

1. Supply Chain Analytics and Data Science

This course focuses on applying statistical and machine learning techniques to supply chain problems. Students learn how to extract actionable insights from large datasets using tools like Python, R, and SQL. Topics include demand forecasting, inventory optimization, route planning, and anomaly detection in supply chain networks.

2. Sustainable Supply Chain Management

This elective explores environmental and social responsibility in supply chains. Students examine carbon footprint reduction strategies, circular economy models, ethical sourcing practices, and compliance with global sustainability standards such as ISO 14001 and the UN Sustainable Development Goals.

3. Global Logistics and International Trade

Designed for students interested in cross-border operations, this course covers international logistics systems, customs regulations, trade finance, maritime and air freight, import/export documentation, and geopolitical risks affecting global supply chains.

4. Supply Chain Innovation and Digital Transformation

This course examines how emerging technologies such as IoT, blockchain, AI, and robotics are transforming traditional supply chain processes. Students explore innovation frameworks, digital twin modeling, smart warehouse automation, and the integration of new tech into existing supply chain infrastructures.

5. Procurement and Supplier Management

This course provides comprehensive training in procurement strategies, supplier evaluation techniques, contract negotiation, vendor relationship management, and strategic sourcing. Students gain hands-on experience through simulations and case studies involving multinational corporations.

6. Operations Research in Supply Chains

Students learn mathematical optimization methods to solve complex supply chain problems. This includes linear programming, network flow models, integer programming, queuing theory, and simulation techniques for decision-making under uncertainty.

7. Risk Management and Business Continuity

This elective prepares students to identify, assess, and mitigate risks in global supply chains. Topics include business continuity planning, disaster recovery strategies, cybersecurity threats, cyber-attacks on supply chain systems, and resilience building techniques.

8. E-commerce and Retail Supply Chain

Students study the unique challenges of online retail logistics, including last-mile delivery optimization, warehouse management, customer experience design, reverse logistics, and demand prediction in dynamic e-commerce environments.

9. Supply Chain Finance

This course explores financial aspects of supply chains, including working capital management, supply chain cost analysis, trade finance, risk-based pricing, and financial modeling for supply chain investments. Students also learn about supply chain financing mechanisms like factoring and invoice discounting.

10. Smart Manufacturing and Industry 4.0

Students explore the intersection of manufacturing and supply chains in the context of Industry 4.0. This includes topics such as smart factories, IoT integration, predictive maintenance, digital twins, and automated supply chain systems.

Project-Based Learning Philosophy

Our department strongly believes in experiential learning through project-based assignments. Students engage in both mini-projects during earlier semesters and a major capstone project in their final year. The goal is to apply theoretical knowledge to real-world scenarios, develop teamwork skills, and build professional portfolios.

Mini-Projects (Semester V)

In Semester V, students work on mini-projects under faculty supervision. These projects are typically team-based and focus on specific aspects of supply chain management such as demand forecasting, supplier evaluation, or route optimization. Projects are selected based on student interests and industry relevance.

Final-Year Thesis/Capstone Project (Semester VII & VIII)

In the final two semesters, students undertake a comprehensive capstone project that integrates all concepts learned throughout the program. Students can choose from industry-sponsored projects or propose their own research questions. Each project is supervised by a faculty mentor and evaluated based on innovation, feasibility, impact, and presentation quality.

Project Selection Process

The selection process involves several stages:

• Ideation Phase: Students brainstorm ideas based on their interests and industry trends.
• Proposal Submission: Detailed project proposals are submitted, including objectives, methodology, timeline, and expected outcomes.
• Mentor Assignment: Faculty mentors are assigned based on expertise alignment.
• Progress Reviews: Regular reviews ensure adherence to timelines and quality standards.
• Presentation and Evaluation: Final presentations are held in front of a panel of faculty members and industry experts.