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Fees
N/A
Placement
93.5%
Avg Package
₹6,50,000
Highest Package
₹12,00,000
Fees
N/A
Placement
93.5%
Avg Package
₹6,50,000
Highest Package
₹12,00,000
Seats
120
Students
320
Seats
120
Students
320
| Semester | Course Code | Course Title | Credit (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | ENG101 | English for Technical Communication | 3-0-0-3 | - |
| 1 | MAT101 | Mathematics I | 4-0-0-4 | - |
| 1 | PHY101 | Physics I | 3-0-0-3 | - |
| 1 | CHE101 | Chemistry I | 3-0-0-3 | - |
| 1 | ESC101 | Engineering Drawing & Computer Graphics | 2-0-2-3 | - |
| 1 | CSE101 | Introduction to Computer Programming | 2-0-2-3 | - |
| 1 | ELE101 | Basic Electrical Circuits | 3-0-0-3 | - |
| 2 | MAT201 | Mathematics II | 4-0-0-4 | MAT101 |
| 2 | PHY201 | Physics II | 3-0-0-3 | PHY101 |
| 2 | CHE201 | Chemistry II | 3-0-0-3 | CHE101 |
| 2 | ELE201 | Electrical Machines & Transformers | 3-0-0-3 | ELE101 |
| 2 | MCH201 | Engineering Mechanics | 3-0-0-3 | - |
| 2 | CSE201 | Data Structures & Algorithms | 2-0-2-3 | CSE101 |
| 3 | MAT301 | Mathematics III | 4-0-0-4 | MAT201 |
| 3 | MCH301 | Strength of Materials | 3-0-0-3 | MCH201 |
| 3 | TME301 | Thermodynamics & Heat Transfer | 3-0-0-3 | - |
| 3 | FME301 | Fluid Mechanics | 3-0-0-3 | - |
| 3 | MCH302 | Machine Design I | 3-0-0-3 | MCH201 |
| 3 | ELE301 | Electrical Circuits & Networks | 3-0-0-3 | ELE101 |
| 4 | MAT401 | Mathematics IV | 4-0-0-4 | MAT301 |
| 4 | MCH401 | Mechanics of Machines | 3-0-0-3 | MCH301 |
| 4 | TME401 | Power Plant Engineering | 3-0-0-3 | TME301 |
| 4 | FME401 | Hydraulic & Pneumatic Systems | 3-0-0-3 | FME301 |
| 4 | MCH402 | Machine Design II | 3-0-0-3 | MCH302 |
| 4 | ELE401 | Control Systems | 3-0-0-3 | ELE301 |
| 5 | MCH501 | Vibration Analysis | 3-0-0-3 | MCH401 |
| 5 | IME501 | Industrial Maintenance Engineering | 3-0-0-3 | - |
| 5 | ELE501 | Digital Electronics & Microprocessors | 3-0-0-3 | ELE401 |
| 5 | TME501 | Industrial Automation | 3-0-0-3 | - |
| 5 | MCH502 | Reliability Engineering | 3-0-0-3 | MCH501 |
| 5 | CSE501 | Database Management Systems | 2-0-2-3 | CSE201 |
| 6 | MCH601 | Predictive Maintenance | 3-0-0-3 | IME501 |
| 6 | ELE601 | Advanced Control Systems | 3-0-0-3 | ELE401 |
| 6 | TME601 | Process Control & Instrumentation | 3-0-0-3 | TME501 |
| 6 | MCH602 | Advanced Materials & Corrosion Engineering | 3-0-0-3 | - |
| 6 | CSE601 | Artificial Intelligence & Machine Learning | 2-0-2-3 | CSE501 |
| 7 | MCH701 | Digital Twin Technology | 3-0-0-3 | MCH601 |
| 7 | IME701 | Advanced Maintenance Management Systems | 3-0-0-3 | - |
| 7 | ELE701 | Industrial IoT & Cybersecurity | 3-0-0-3 | ELE501 |
| 7 | MCH702 | Sustainable Engineering Practices | 3-0-0-3 | - |
| 7 | CSE701 | Big Data Analytics for Maintenance | 2-0-2-3 | CSE601 |
| 8 | MCH801 | Final Year Capstone Project | 4-0-0-4 | - |
| 8 | IME801 | Research & Development Internship | 2-0-0-2 | - |
| 8 | ELE801 | Capstone Thesis | 4-0-0-4 | - |
| 8 | MCH802 | Professional Ethics & Leadership | 2-0-0-2 | - |
Predictive Maintenance: This course introduces students to predictive maintenance concepts, including vibration analysis, thermal imaging, and acoustic monitoring. Students learn how to implement machine learning algorithms for fault detection and diagnosis in industrial environments. The course emphasizes real-world applications through case studies and lab simulations.
Industrial Automation: Focused on automation technologies used in modern manufacturing processes, this course covers programmable logic controllers (PLCs), human-machine interfaces (HMIs), and distributed control systems (DCS). Practical sessions involve programming PLCs and designing automation solutions for industrial applications.
Digital Twin Technology: This advanced course explores the concept of digital twins—virtual replicas of physical systems used to simulate, analyze, and optimize performance. Students learn to build and deploy digital twins using software tools such as Siemens NX, MATLAB/Simulink, and Unity 3D.
Advanced Materials & Corrosion Engineering: Designed to deepen students' understanding of material science, this course covers corrosion mechanisms, protective coatings, and advanced materials used in harsh industrial environments. Hands-on experiments include corrosion testing, hardness measurements, and material characterization techniques.
Process Control & Instrumentation: This course focuses on control systems and instrumentation used in chemical and process industries. Students study process dynamics, feedback control, sensors, actuators, and control valves. Practical lab sessions involve designing and implementing control loops for industrial processes.
Industrial IoT & Cybersecurity: Addressing the growing importance of cybersecurity in industrial settings, this course covers IoT architectures, network security protocols, and threat detection systems. Students learn to secure industrial networks against cyber attacks and protect critical infrastructure from digital threats.
Big Data Analytics for Maintenance: This elective introduces students to data analytics tools and techniques used in predictive maintenance and asset management. Topics include data preprocessing, statistical modeling, regression analysis, and visualization using Python and R programming languages.
Sustainable Engineering Practices: Emphasizing sustainability in engineering design and operations, this course covers lifecycle assessment, energy efficiency, waste reduction strategies, and green manufacturing techniques. Students engage in projects that address environmental challenges through sustainable engineering solutions.
Research & Development Internship: This practical component provides students with hands-on experience in research labs or industry R&D centers. Under supervision, students contribute to ongoing research projects, develop new methodologies, and present findings at academic or industrial forums.
Capstone Thesis: The final year capstone project allows students to apply integrated knowledge gained throughout the program to solve a real-world engineering problem. Students work closely with faculty mentors to design, execute, and document their research, culminating in a comprehensive thesis and presentation.
The department's philosophy on project-based learning is centered around experiential education, where students actively participate in solving complex engineering problems using multidisciplinary approaches. The curriculum incorporates both mini-projects and a final-year capstone project to ensure comprehensive skill development.
Mini-projects are undertaken during the third and fourth semesters, focusing on specific aspects of industrial maintenance such as equipment diagnostics, automation implementation, or safety audits. These projects are evaluated based on technical execution, teamwork, presentation skills, and documentation quality.
The final-year capstone project spans the entire eighth semester and involves a comprehensive investigation into a significant issue in industrial maintenance. Students select topics aligned with their interests or industry needs, under the guidance of faculty mentors from relevant departments. The project includes literature review, experimental design, data analysis, and solution development, followed by a formal presentation and defense.
Project selection is facilitated through an online portal where students propose ideas, receive feedback, and collaborate with mentors to refine their concepts. Faculty members from various disciplines—mechanical, electrical, computer science, and industrial engineering—are involved in mentoring these projects, ensuring interdisciplinary exposure and relevance to current industry trends.
