Curriculum
The Mechanical Engineering curriculum at Jaypee Institute of Information Technology Noida is meticulously designed to provide students with a comprehensive understanding of core principles while fostering innovation and practical application. The program spans eight semesters, each building upon the previous one to ensure a progressive learning experience.
Course Structure Overview
The curriculum integrates foundational sciences, core engineering subjects, departmental electives, and advanced specializations. Core subjects form the backbone of the program, covering essential areas such as thermodynamics, fluid mechanics, heat transfer, and machine design. Departmental electives allow students to explore specialized domains based on their interests and career aspirations.
Year-wise Course Listing
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| I | MATH101 | Engineering Mathematics I | 3-1-0-4 | None |
| I | PHYS101 | Physics for Engineers | 3-1-0-4 | None |
| I | MECH101 | Introduction to Mechanical Engineering | 2-0-2-3 | None |
| I | CSE101 | Programming for Engineers | 2-0-2-3 | None |
| I | ENG101 | English for Technical Communication | 2-0-0-2 | None |
| I | PHY101L | Physics Laboratory | 0-0-3-1 | None |
| II | MATH201 | Engineering Mathematics II | 3-1-0-4 | MATH101 |
| II | CHEM101 | Chemistry for Engineers | 3-1-0-4 | None |
| II | MECH201 | Mechanics of Materials | 3-1-0-4 | MATH101, PHYS101 |
| II | MECH202 | Thermodynamics | 3-1-0-4 | MATH101, PHYS101 |
| II | MECH203 | Fluid Mechanics | 3-1-0-4 | MATH101, PHYS101 |
| II | CSE201 | Data Structures and Algorithms | 3-1-0-4 | CSE101 |
| III | MATH301 | Engineering Mathematics III | 3-1-0-4 | MATH201 |
| III | MECH301 | Heat Transfer | 3-1-0-4 | MECH202, MECH203 |
| III | MECH302 | Mechanics of Machines | 3-1-0-4 | MECH201 |
| III | MECH303 | Manufacturing Processes | 3-1-0-4 | MECH201 |
| III | MECH304 | Machine Design | 3-1-0-4 | MECH201, MECH302 |
| IV | MATH401 | Engineering Mathematics IV | 3-1-0-4 | MATH301 |
| IV | MECH401 | Dynamics | 3-1-0-4 | MECH201, MECH302 |
| IV | MECH402 | Control Systems | 3-1-0-4 | MATH401, MECH401 |
| IV | MECH403 | Advanced Manufacturing | 3-1-0-4 | MECH303 |
| V | MECH501 | Artificial Intelligence in Mechanical Systems | 3-1-0-4 | MECH402, CSE201 |
| V | MECH502 | Sustainable Energy Technologies | 3-1-0-4 | MECH202 |
| V | MECH503 | Biomechanics & Medical Devices | 3-1-0-4 | MECH301, MECH304 |
| V | MECH504 | Aerodynamics & Propulsion Systems | 3-1-0-4 | MECH203 |
| V | MECH505 | Nanotechnology & Advanced Materials | 3-1-0-4 | MECH303 |
| V | MECH506 | Robotics & Automation | 3-1-0-4 | MECH401, MECH402 |
| VI | MECH601 | Project Management | 2-0-2-3 | MECH501 |
| VI | MECH602 | Research Methodology | 2-0-2-3 | None |
| VI | MECH603 | Advanced Thermodynamics | 3-1-0-4 | MECH202 |
| VII | MECH701 | Capstone Project I | 2-0-6-5 | MECH501, MECH502, MECH503, MECH504, MECH505, MECH506 |
| VIII | MECH801 | Capstone Project II | 2-0-6-5 | MECH701 |
Advanced Departmental Electives
The department offers several advanced elective courses that allow students to specialize in emerging areas within mechanical engineering. These courses are designed to provide depth and breadth of knowledge required for tackling real-world challenges.
- Machine Learning for Mechanical Engineers: This course explores how machine learning algorithms can be applied to optimize mechanical systems, predict failures, and enhance performance. Students learn to implement ML models using Python libraries such as scikit-learn and TensorFlow.
- Renewable Energy Systems: Focuses on solar, wind, hydroelectric, and geothermal energy technologies. The course covers design principles, efficiency analysis, and integration strategies for renewable systems in mechanical applications.
- Biofluid Mechanics: Combines fluid dynamics with biological systems to understand blood flow, respiratory mechanics, and other physiological processes. Students engage in computational modeling using ANSYS Fluent and STAR-CD.
- Smart Manufacturing Technologies: Covers Industry 4.0 concepts including IoT integration, digital twins, and smart factory automation. Students work on real-time data analysis projects involving sensors and actuators.
- Advanced Materials Characterization: Teaches students how to analyze material properties using advanced techniques such as XRD, SEM, TEM, and FTIR. The course includes hands-on lab sessions with state-of-the-art equipment.
- Finite Element Analysis in Mechanical Engineering: Provides an in-depth understanding of FEM concepts and applications. Students use software tools like ABAQUS and ANSYS to solve complex engineering problems.
- Computational Fluid Dynamics: Explores numerical methods for solving fluid flow problems. The course covers CFD theory, grid generation, turbulence modeling, and simulation of real-world scenarios using OpenFOAM and Fluent.
- Advanced Robotics & Control Systems: Focuses on advanced control strategies for robotic systems including PID controllers, state-space models, and adaptive control techniques. Students build and program autonomous robots using ROS (Robot Operating System).
- Energy Storage Technologies: Reviews current energy storage technologies such as batteries, supercapacitors, and hydrogen fuel cells. The course includes laboratory experiments on battery testing and performance optimization.
- Sustainable Design & Green Manufacturing: Emphasizes eco-friendly design principles and green manufacturing practices. Students learn about life cycle assessment (LCA), carbon footprint reduction, and sustainable product development.
Project-Based Learning Philosophy
The department's philosophy on project-based learning is centered around experiential education and real-world problem-solving. Mini-projects are assigned during the second and third years to reinforce theoretical concepts through practical implementation. These projects often involve collaboration with industry partners, providing students with exposure to professional environments.
Final-year thesis/capstone projects span two semesters and are typically conducted in teams under the guidance of faculty mentors. Students select their projects based on personal interests and career aspirations, ensuring relevance and motivation. Evaluation criteria include innovation, technical depth, presentation quality, and project outcomes. The department maintains a database of potential projects provided by industry partners, academic researchers, and alumni.
Mini-Projects Structure
Mini-projects are assigned in the second and third years to reinforce concepts learned in class. Each project lasts approximately 6-8 weeks and involves working in small groups of 3-5 students. Projects are selected from a list curated by faculty members based on relevance to current industry trends and student interests.
Each mini-project is evaluated based on:
- Technical Implementation (40%)
- Problem Solving Skills (20%)
- Presentation Quality (20%)
- Team Collaboration (20%)
Final-Year Thesis/Capstone Project
The final-year thesis project is a comprehensive endeavor that integrates all knowledge and skills acquired during the program. Students work on either individual or team-based projects under faculty supervision for a duration of 12-16 weeks.
Project selection involves:
- Interest-based matching with faculty mentors
- Industry collaboration opportunities
- Research-oriented topics aligned with departmental strengths
Evaluation criteria for the final project include:
- Originality and Innovation (30%)
- Technical Depth and Accuracy (30%)
- Presentation and Documentation (20%)
- Impact and Relevance (20%)
The department facilitates project selection through a mentorship system where students are paired with faculty members based on their interests and expertise areas.