Course Structure Overview
The Industrial Maintenance program at K L Polytechnic is designed to provide a comprehensive understanding of industrial systems and their maintenance. The curriculum spans four years, with each semester containing a mix of core subjects, departmental electives, science electives, and laboratory sessions.
| Year | Semester | Course Code | Course Title | Credit (L-T-P-C) | Pre-requisites |
|---|---|---|---|---|---|
| 1 | I | ENG101 | English for Technical Communication | 3-0-0-3 | - |
| MAT101 | Mathematics I | 4-0-0-4 | - | ||
| 1 | II | MAT102 | Mathematics II | 4-0-0-4 | MAT101 |
| PHY101 | Physics for Engineers | 3-0-0-3 | - | ||
| 2 | III | CHE101 | Chemistry for Engineers | 3-0-0-3 | - |
| MAT201 | Mathematics III | 4-0-0-4 | MAT102 | ||
| 2 | IV | ENG201 | Engineering Mechanics | 3-0-0-3 | - |
| PHY201 | Thermodynamics | 3-0-0-3 | PHY101 | ||
| 3 | V | MAT301 | Mathematics IV | 4-0-0-4 | MAT201 |
| CSE101 | Introduction to Computer Programming | 3-0-0-3 | - | ||
| 3 | VI | ECE101 | Electrical Circuits and Networks | 4-0-0-4 | - |
| MEC101 | Mechanics of Materials | 3-0-0-3 | - | ||
| 4 | VII | MEC201 | Machine Design | 4-0-0-4 | MEC101 |
| ECE201 | Control Systems | 4-0-0-4 | ECE101 | ||
| 4 | VIII | MEC301 | Advanced Maintenance Techniques | 4-0-0-4 | MEC201 |
| ECE301 | Industrial Automation | 4-0-0-4 | ECE201 |
Advanced Departmental Electives
Departmental electives in the Industrial Maintenance program offer students opportunities to specialize in advanced topics relevant to industry needs. These courses are designed to deepen understanding and provide practical skills for real-world applications.
The course Advanced Maintenance Techniques explores modern methods of maintenance including preventive, predictive, and condition-based strategies. Students learn about failure analysis, root cause identification, and optimization techniques used in industrial settings.
Predictive Maintenance Using Data Analytics integrates statistical methods and machine learning algorithms to forecast equipment failures. This course emphasizes practical applications using real datasets from manufacturing plants and includes hands-on sessions with data visualization tools.
The Industrial Robotics and Automation course introduces students to robot programming, sensor integration, and automation systems used in modern manufacturing environments. Practical sessions include working with industrial robots and simulation software.
Process Control Systems focuses on the design and implementation of control systems in industrial processes. Students study feedback control mechanisms, PID controllers, and process dynamics through laboratory experiments and simulations.
Quality Assurance in Manufacturing covers quality management principles, statistical process control, and Six Sigma methodologies. This course prepares students to implement quality improvement initiatives in production environments.
Maintenance Project Management teaches project planning, resource allocation, risk assessment, and budgeting for maintenance projects. Students engage in case studies of actual industrial projects and develop comprehensive project plans.
Environmental and Safety Management addresses environmental regulations, occupational health standards, and safety protocols in industrial settings. This course includes modules on hazard identification, emergency response planning, and compliance auditing.
Advanced Materials for Maintenance delves into material selection criteria, corrosion prevention, and advanced materials used in industrial applications. Students explore new developments in coatings, composites, and smart materials.
Energy Efficiency in Industrial Systems focuses on optimizing energy consumption in manufacturing plants. This course covers energy auditing, renewable energy integration, and sustainable practices in industrial operations.
Industrial Data Analytics introduces students to big data technologies, machine learning applications, and data-driven decision making in maintenance environments. Students gain experience with platforms like Python, R, and specialized analytics software.
Smart Manufacturing Technologies explores Industry 4.0 concepts including IoT, digital twins, and cyber-physical systems. This course provides insights into future trends and technologies shaping the manufacturing landscape.
Project-Based Learning Philosophy
The Industrial Maintenance program emphasizes project-based learning as a core pedagogical approach. This philosophy encourages students to apply theoretical knowledge to practical problems, fostering critical thinking and problem-solving skills.
Mini-projects are assigned in early semesters to help students develop foundational skills. These projects involve designing simple maintenance solutions for basic equipment, working with standard tools and materials, and presenting findings to peers and faculty.
The final-year thesis/capstone project represents the culmination of student learning. Students select a topic relevant to industry needs or personal interest, often in collaboration with industry partners. The process includes literature review, experimental design, data collection, analysis, and presentation.
Faculty mentors guide students throughout the project lifecycle, providing expertise in research methodologies, technical aspects, and professional development. Regular meetings and feedback sessions ensure that projects meet academic standards and industry relevance.
Project selection is based on student interests, faculty availability, and resource constraints. Students may propose topics aligned with their career aspirations or work on problems identified by industry partners. The final project portfolio includes a written report, presentation slides, and demonstration materials.