Comprehensive Course Schedule and Structure

Detailed Departmental Elective Courses

These advanced electives provide students with specialized knowledge and skills in emerging areas of operations management:

• Data Analytics for Operations: This course equips students with tools and techniques to analyze large datasets using statistical methods and machine learning algorithms. It covers predictive modeling, data visualization, and decision support systems. Students learn how to extract actionable insights from complex data sources and apply them in real-world operational settings.
• Lean & Six Sigma Tools: Focused on process improvement methodologies, this course teaches students how to eliminate waste and improve quality using structured problem-solving approaches. Topics include DMAIC framework, value stream mapping, and statistical tools for process analysis.
• Risk Assessment in Operations: Students explore the identification, evaluation, and mitigation of operational risks across different industries. This includes financial risk modeling, supply chain vulnerabilities, and operational resilience planning.
• Innovation & Change Management: This course addresses how organizations manage innovation initiatives and adapt to change. It covers design thinking, organizational behavior, and strategies for fostering continuous improvement in dynamic environments.
• Sustainability in Operations: Emphasizing environmental responsibility, this elective explores green operations practices, carbon footprint reduction, and sustainable supply chains. Students learn how to balance profitability with ecological sustainability.
• Service Operations: Focuses on the unique challenges of service delivery systems. Students study service quality measurement, customer experience design, and operational excellence in service industries such as hospitality, healthcare, and finance.
• Digital Manufacturing: Integrates digital technologies into manufacturing processes. Topics include Industrial IoT, robotics, automation, and smart factory concepts. Students gain hands-on experience with simulation software and real-world applications.
• Supply Chain Optimization: Covers strategic aspects of supply chain design and optimization. Students learn about supplier selection, logistics network design, demand forecasting, and risk management in global supply chains.
• Operations Research: Introduces mathematical modeling techniques used to solve complex operational problems. Emphasis is placed on linear programming, integer programming, network flows, and queuing theory.
• Simulation Modeling: Teaches students how to build and run simulations of operational systems using tools like Arena and AnyLogic. Applications include inventory control, queue management, and capacity planning.

Project-Based Learning Philosophy

The department follows a robust project-based learning approach that emphasizes active engagement, critical thinking, and practical application of knowledge. Mini-projects are introduced from the third semester onwards, allowing students to apply theoretical concepts in simulated real-world scenarios. Each project is assigned a faculty mentor who provides guidance throughout the process.

Students select their projects based on personal interest, industry relevance, and available resources. The selection process involves submitting proposals that undergo peer review and faculty approval. Projects are typically completed over two semesters and culminate in a formal presentation and written report.

The final-year thesis/capstone project represents the culmination of the student’s learning journey. It is an independent research endeavor that requires students to identify a significant operational challenge, propose innovative solutions, and present findings to a panel of experts. Faculty mentors guide students through every stage, from problem definition to solution implementation.

Evaluation criteria for projects include innovation, feasibility, impact assessment, documentation quality, and presentation skills. A dedicated committee reviews each project and assigns grades based on these parameters. Successful projects often lead to publications, patents, or commercialization opportunities.