Course Structure Across 8 Semesters
| Semester | Course Code | Full Course Title | Credit (L-T-P-C) | Pre-requisites |
|---|---|---|---|---|
| 1 | MATH101 | Mathematics I | 3-1-0-4 | None |
| 1 | PHYS101 | Physics for Engineering | 3-1-0-4 | None |
| 1 | MECH101 | Introduction to Mechanical Engineering | 2-0-0-2 | None |
| 1 | CS101 | Programming Fundamentals | 3-0-2-4 | None |
| 1 | ECON101 | Introduction to Economics | 3-0-0-3 | None |
| 2 | MATH201 | Mathematics II | 3-1-0-4 | MATH101 |
| 2 | PHYS201 | Thermodynamics and Heat Transfer | 3-1-0-4 | PHYS101 |
| 2 | MECH201 | Mechanics of Materials | 3-1-0-4 | MECH101 |
| 2 | CS201 | Data Structures and Algorithms | 3-0-2-4 | CS101 |
| 2 | ECON201 | Microeconomics | 3-0-0-3 | ECON101 |
| 3 | MATH301 | Statistics and Probability | 3-1-0-4 | MATH201 |
| 3 | PHYS301 | Electromagnetism | 3-1-0-4 | PHYS201 |
| 3 | MECH301 | Fluid Mechanics | 3-1-0-4 | MECH201 |
| 3 | CS301 | Database Management Systems | 3-0-2-4 | CS201 |
| 3 | ECON301 | Macroeconomics | 3-0-0-3 | ECON201 |
| 4 | MATH401 | Numerical Methods | 3-1-0-4 | MATH301 |
| 4 | PHYS401 | Quantum Physics | 3-1-0-4 | PHYS301 |
| 4 | MECH401 | Mechanical Design | 3-1-0-4 | MECH301 |
| 4 | CS401 | Software Engineering | 3-0-2-4 | CS301 |
| 4 | ECON401 | Development Economics | 3-0-0-3 | ECON301 |
| 5 | OPM501 | Operations Research | 3-1-0-4 | MATH401 |
| 5 | OPM502 | Supply Chain Management | 3-1-0-4 | ECON401 |
| 5 | OPM503 | Quality Control Systems | 3-1-0-4 | MECH401 |
| 5 | OPM504 | Process Modeling and Simulation | 3-0-2-4 | CS401 |
| 6 | OPM601 | Data Analytics for Operations | 3-1-0-4 | OPM501 |
| 6 | OPM602 | Lean and Agile Manufacturing | 3-1-0-4 | OPM502 |
| 6 | OPM603 | Sustainable Operations | 3-1-0-4 | OPM503 |
| 6 | OPM604 | Project Management | 3-1-0-4 | OPM504 |
| 7 | OPM701 | Advanced Operations Strategy | 3-1-0-4 | OPM601 |
| 7 | OPM702 | Digital Transformation in Operations | 3-1-0-4 | OPM602 |
| 7 | OPM703 | Smart Manufacturing Systems | 3-1-0-4 | OPM603 |
| 7 | OPM704 | Operations in E-commerce | 3-1-0-4 | OPM604 |
| 8 | OPM801 | Capstone Project | 6-0-0-6 | All previous OPM courses |
| 8 | OPM802 | Internship | 3-0-0-3 | OPM704 |
Advanced Departmental Electives
The department offers a range of advanced elective courses designed to deepen student understanding and prepare them for specialized roles in various industries. These courses are tailored to align with current trends and industry demands, ensuring relevance and practical application.
Machine Learning for Supply Chain Optimization: This course introduces students to machine learning techniques specifically applied to supply chain problems. Topics include demand forecasting, inventory optimization, route planning, and risk analysis using ML algorithms. Students will work on real-world datasets provided by industry partners.
Data Mining Techniques for Decision Support: Focused on extracting actionable insights from large volumes of operational data, this course covers clustering, classification, association rules, and anomaly detection. Students gain hands-on experience with tools like Python and R, applying them to operational decision-making scenarios.
Big Data Platforms and Tools: As organizations increasingly rely on big data for operational decisions, students learn to use platforms like Hadoop, Spark, and Kafka. The course emphasizes practical implementation of data pipelines and real-time analytics in production environments.
Supply Chain Risk Management: This elective explores how to identify, assess, and mitigate risks in global supply chains. Students examine case studies involving natural disasters, geopolitical issues, and cyber threats, developing mitigation strategies through simulation exercises.
Sustainable Operations and Circular Economy: Addressing environmental challenges, this course teaches students how to design operations that minimize waste and maximize resource efficiency. It covers lifecycle assessment, green logistics, and circular economy principles applicable across industries.
Operations in Healthcare Systems: Designed for those interested in the healthcare sector, this course examines how operational principles apply to hospital management, pharmaceutical supply chains, medical device manufacturing, and public health delivery systems.
Operations in Public Sector and NGOs: This course explores how operational strategies can be adapted for non-profit and governmental organizations. Students learn about resource allocation, program evaluation, and performance measurement in the context of social impact initiatives.
Digital Transformation in Operations: Covering emerging technologies such as IoT, AI, and blockchain, this course provides a deep dive into how digital innovation is reshaping operational practices across sectors. Students develop prototypes for digital solutions using available platforms and tools.
Process Automation and Robotics: This elective focuses on automation technologies in manufacturing environments. Students learn about robotic process automation (RPA), industrial robots, and AI-powered systems that enhance productivity and reduce human error.
Lean Six Sigma for Operations Excellence: Combining lean principles with Six Sigma methodologies, this course teaches students how to eliminate waste and improve quality in operational processes. Through simulations and case studies, students learn to apply DMAIC (Define, Measure, Analyze, Improve, Control) frameworks.
Operations Strategy and Competitive Advantage: Students explore how strategic decisions in operations influence competitive positioning. The course combines theoretical concepts with real-world examples from Fortune 500 companies, focusing on innovation, agility, and operational excellence.
Financial Modeling for Operations: This interdisciplinary course bridges finance and operations by teaching students how to model financial performance of operational activities. Topics include cost-benefit analysis, budgeting, ROI evaluation, and investment decisions in operational contexts.
Business Intelligence and Analytics: Emphasizing the use of data-driven insights for operational decision-making, this course covers dashboards, reporting tools, visualization techniques, and KPI development tailored to operational environments.
Global Operations Management: With an emphasis on international markets, this course examines cross-cultural challenges in operations management, global sourcing strategies, multinational supply chains, and regulatory compliance issues.
Customer Experience Design for Operations: Students learn how to integrate customer experience design into operational frameworks. The course covers user journey mapping, service blueprinting, feedback loops, and continuous improvement processes that enhance both internal efficiency and external satisfaction.
Operations in E-commerce and Retail: Focused on digital commerce ecosystems, this course explores demand forecasting, inventory management, order fulfillment, logistics optimization, and omnichannel strategies in modern retail environments.
Project-Based Learning Philosophy
At BHABHA MANAGEMENT RESEARCH INSTITUTE, we believe that learning through doing is the most effective way to develop operational skills. Our approach to project-based learning integrates theoretical knowledge with practical application, encouraging students to engage deeply with real-world challenges.
Mini-projects are introduced in early semesters and progressively increase in complexity. These projects are typically completed within 2–4 weeks and involve small groups of 3–5 students working under faculty supervision. They focus on specific operational problems or scenarios, allowing students to apply learned concepts directly.
The final-year thesis/capstone project represents the culmination of the student’s academic journey. Students choose a topic related to their specialization area and work closely with a faculty mentor for 4–6 months. The project must include a literature review, methodology, implementation, analysis, and recommendations. It often results in publishable work or industry-sponsored innovations.
Selection of projects and mentors is done through a structured process involving interest surveys, academic performance reviews, and faculty availability. Students are encouraged to propose topics aligned with their career goals or current industry trends, ensuring relevance and personal investment.
Evaluation criteria for projects emphasize not only technical execution but also communication skills, teamwork, ethical considerations, and innovation potential. Each project is assessed through presentations, written reports, peer reviews, and final evaluations by a panel of faculty members and industry experts.