Comprehensive Course Structure and Curriculum
The curriculum for the Operations program at Roorkee College Of Management And Computer Applications Roorkee is meticulously designed to provide students with a balanced mix of foundational knowledge, technical skills, and practical experience. The eight-semester structure ensures a progressive learning journey that builds upon prior knowledge while preparing students for advanced specialization.
Semester-Wise Course Structure
| Semester | Course Code | Full Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | ENG101 | Engineering Mathematics I | 3-0-0-3 | - |
| 1 | PHY101 | Physics for Engineers | 3-0-0-3 | - |
| 1 | CHE101 | Chemistry for Engineers | 3-0-0-3 | - |
| 1 | BIO101 | Biology for Engineers | 2-0-0-2 | - |
| 1 | CS101 | Introduction to Computer Programming | 3-0-0-3 | - |
| 1 | ECON101 | Introduction to Economics | 2-0-0-2 | - |
| 1 | MATH101 | Calculus and Linear Algebra | 3-0-0-3 | - |
| 2 | ENG102 | Engineering Mathematics II | 3-0-0-3 | ENG101 |
| 2 | MATH102 | Probability and Statistics for Engineers | 3-0-0-3 | MATH101 |
| 2 | PHY102 | Thermodynamics and Heat Transfer | 3-0-0-3 | PHY101 |
| 2 | MAT101 | Materials Science and Engineering | 3-0-0-3 | CHE101 |
| 2 | CS102 | Data Structures and Algorithms | 3-0-0-3 | CS101 |
| 2 | ECON102 | Microeconomics | 2-0-0-2 | ECON101 |
| 3 | OPM101 | Introduction to Operations Management | 2-0-0-2 | - |
| 3 | MATH103 | Operations Research I | 3-0-0-3 | MATH102 |
| 3 | MECH101 | Fluid Mechanics and Hydraulics | 3-0-0-3 | PHY102 |
| 3 | CS103 | Database Management Systems | 3-0-0-3 | CS102 |
| 3 | ECON103 | Macroeconomics | 2-0-0-2 | ECON102 |
| 4 | OPM102 | Operations Planning and Control | 2-0-0-2 | OPM101 |
| 4 | MATH104 | Advanced Operations Research II | 3-0-0-3 | MATH103 |
| 4 | MECH102 | Mechanics of Materials | 3-0-0-3 | MAT101 |
| 4 | CS104 | Software Engineering | 3-0-0-3 | CS103 |
| 4 | ECON104 | Business Finance | 2-0-0-2 | ECON103 |
| 5 | OPM201 | Supply Chain Management | 2-0-0-2 | OPM102 |
| 5 | MATH105 | Stochastic Processes in Operations | 3-0-0-3 | MATH104 |
| 5 | MECH103 | Industrial Engineering Principles | 3-0-0-3 | MECH102 |
| 5 | CS105 | Machine Learning for Operations | 3-0-0-3 | CS104 |
| 5 | ECON105 | Industrial Organization | 2-0-0-2 | ECON104 |
| 6 | OPM202 | Quality Management Systems | 2-0-0-2 | OPM201 |
| 6 | MATH106 | Decision Analysis in Operations | 3-0-0-3 | MATH105 |
| 6 | MECH104 | Production Planning and Scheduling | 3-0-0-3 | MECH103 |
| 6 | CS106 | Big Data Analytics for Operations | 3-0-0-3 | CS105 |
| 6 | ECON106 | Corporate Strategy | 2-0-0-2 | ECON105 |
| 7 | OPM301 | Digital Operations and Automation | 2-0-0-2 | OPM202 |
| 7 | MATH107 | Advanced Analytics in Operations | 3-0-0-3 | MATH106 |
| 7 | MECH105 | Lean Manufacturing Principles | 3-0-0-3 | MECH104 |
| 7 | CS107 | Internet of Things (IoT) in Operations | 3-0-0-3 | CS106 |
| 7 | ECON107 | Economic Analysis of Operations | 2-0-0-2 | ECON106 |
| 8 | OPM302 | Operations Strategy and Innovation | 2-0-0-2 | OPM301 |
| 8 | MATH108 | Operations Research Capstone | 3-0-0-3 | MATH107 |
| 8 | MECH106 | Project Management in Operations | 3-0-0-3 | MECH105 |
| 8 | CS108 | Capstone Project in Operations | 3-0-0-3 | CS107 |
| 8 | ECON108 | Business Ethics and Sustainability | 2-0-0-2 | ECON107 |
Detailed Departmental Elective Courses
The department offers a rich array of advanced departmental electives that allow students to tailor their learning experience based on their interests and career aspirations. These courses are designed to deepen understanding in specialized areas while providing hands-on experience with cutting-edge technologies and methodologies.
1. Machine Learning for Operations
This course introduces students to the application of machine learning techniques in solving complex operational problems. It covers supervised and unsupervised learning models, neural networks, and reinforcement learning algorithms tailored for operations management. Students learn how to implement these methods using Python and TensorFlow.
2. Big Data Analytics for Operations
This elective explores the role of big data in modern operations management. Students study distributed computing frameworks like Hadoop and Spark, data visualization tools such as Tableau and Power BI, and predictive modeling techniques for operational analytics. Practical assignments involve analyzing large datasets from real-world companies.
3. Lean Manufacturing Principles
This course focuses on the principles and practices of lean manufacturing, including value stream mapping, 5S methodology, Kaizen events, and continuous improvement. Students engage in simulations and case studies to understand how lean concepts can be applied across industries.
4. Supply Chain Analytics
This elective delves into the analytical tools used in supply chain management. Topics include demand forecasting, inventory optimization, transportation modeling, and risk analysis. Students work with real-world datasets and industry software to develop practical skills in supply chain analytics.
5. Digital Operations and Automation
This course examines how digital technologies are transforming operations across sectors. It covers Industry 4.0 concepts, IoT integration, robotic process automation (RPA), and cyber-physical systems. Students gain hands-on experience through lab sessions and project work.
6. Healthcare Operations Management
This course applies operational principles to healthcare settings. It covers patient flow optimization, resource allocation in hospitals, quality improvement initiatives, and health informatics. Case studies from leading healthcare institutions provide practical insights.
7. Service Delivery Excellence
This elective focuses on the design and management of service systems. Students learn about service blueprinting, customer experience mapping, service quality measurement, and innovation in service delivery. Real-world projects with service providers enhance learning outcomes.
8. Sustainable Supply Chains
This course addresses sustainability challenges in supply chains. It covers green logistics, carbon footprint reduction, circular economy principles, and environmental impact assessment. Students develop strategies for creating sustainable operations that balance economic viability with ecological responsibility.
9. Operations Strategy and Innovation
This advanced course explores how organizations can align their operational capabilities with strategic objectives. It covers innovation management, change leadership, organizational design, and competitive advantage through operational excellence. Students engage in strategic planning exercises and simulations.
10. Project Management in Operations
This elective builds on foundational project management knowledge by focusing on operational contexts. It covers project selection criteria, resource planning, risk management, and performance evaluation in complex operations environments. Students apply methodologies like Agile and Scrum to real-world scenarios.
Project-Based Learning Philosophy
The Operations program at Roorkee College Of Management And Computer Applications Roorkee places a strong emphasis on project-based learning as a core pedagogical approach. This methodology is designed to bridge the gap between theoretical knowledge and practical application, ensuring that students develop critical thinking and problem-solving skills essential for success in their careers.
Mini-Projects Structure
Mini-projects are integrated throughout the curriculum, starting from the second semester. These projects are typically completed in groups of 3-5 students and last for 4-6 weeks. Each project is assigned by a faculty member or industry partner and focuses on a specific operational challenge or opportunity.
The evaluation criteria for mini-projects include:
- Problem Definition: Clarity of the problem statement and relevance to real-world operations challenges.
- Methodology: Appropriateness of analytical methods and tools used.
- Data Analysis: Quality and depth of data interpretation and insights derived.
- Recommendations: Feasibility, innovation, and impact of proposed solutions.
- Presentation Skills: Clarity, professionalism, and effectiveness of communication.
Final-Year Thesis/Capstone Project
The final-year capstone project is a comprehensive endeavor that requires students to integrate all knowledge gained during their undergraduate studies. It involves working closely with a faculty mentor and potentially an industry partner on a significant operational challenge.
Students can choose from several pre-defined topics or propose their own, subject to approval by the departmental advisory board. The project spans an entire semester and results in a detailed report, a presentation, and a demonstration of the implemented solution.
The scope of the capstone project includes:
- Problem identification and literature review
- Data collection and analysis using appropriate tools
- Development of innovative solutions or improvements
- Implementation plan and feasibility assessment
- Final presentation to faculty and industry experts
Project Selection Process
The project selection process ensures that students choose topics aligned with their interests, career goals, and departmental expertise. Students are encouraged to explore various options through consultations with faculty mentors and industry partners.
Faculty members provide guidance on selecting projects that offer meaningful learning experiences while allowing students to contribute significantly to the operational challenges faced by organizations.