Comprehensive Course List

Advanced departmental elective courses are designed to deepen students' understanding of specialized topics within industrial maintenance. These courses include Data Analytics for Maintenance, which explores how big data and machine learning can be applied to predict equipment failures and optimize maintenance schedules. Students learn tools like Python, R, and MATLAB for data analysis.

Automation and Robotics introduces students to robotic systems used in industrial environments. The course covers programming, sensor integration, and automation design principles. It includes hands-on lab sessions where students build and test simple robotic systems.

Maintenance of Power Systems focuses on the operation and maintenance of electrical systems including transformers, generators, and power distribution networks. Students study protection schemes, fault analysis, and system reliability.

Industrial Instrumentation delves into sensors, transmitters, and control instruments used in process industries. Emphasis is placed on calibration, troubleshooting, and integration of instrumentation with control systems.

Asset Management Systems teaches students how to manage industrial assets throughout their lifecycle. Topics include asset valuation, depreciation methods, maintenance planning, and performance metrics.

Predictive Maintenance Techniques explores modern approaches to maintenance using predictive models, condition monitoring, and real-time data analysis. Students gain experience with software tools like MATLAB, SCADA systems, and IoT platforms.

Safety and Risk Management covers safety protocols, hazard identification, risk assessment techniques, and regulatory compliance in industrial settings. The course includes practical exercises in emergency response planning and safety audits.

Environmental Impact Assessment addresses the environmental consequences of industrial operations and strategies for sustainable maintenance practices. Students learn about environmental regulations, waste management, and green technologies.

Advanced Control Systems builds upon basic control theory to explore complex systems including nonlinear controls, state-space models, and adaptive control. It includes simulation-based learning using industry-standard software.

Research Methodology prepares students for conducting independent research in industrial maintenance. The course covers literature review techniques, hypothesis formulation, experimental design, and data interpretation methods.

Quality Assurance in Maintenance focuses on maintaining quality standards in maintenance operations. Students study ISO certifications, quality control tools, root cause analysis, and continuous improvement methodologies.

Green Maintenance Practices emphasizes environmentally sustainable approaches to industrial maintenance. Topics include energy efficiency, waste reduction, recycling strategies, and green certification programs.

Mechanical Design covers principles of mechanical engineering design relevant to industrial maintenance. Students learn about material selection, stress analysis, and design optimization techniques using CAD tools.

The philosophy of project-based learning in the department is centered on fostering innovation, collaboration, and practical problem-solving skills among students. Projects are structured to mirror real-world challenges faced by industry professionals, encouraging students to apply theoretical knowledge to tangible situations.

Mini-projects are undertaken during the third and fourth semesters, with each student working individually or in small teams under faculty supervision. These projects typically span 2-3 months and involve designing, implementing, and documenting solutions to maintenance-related problems.

The final-year thesis/capstone project is a comprehensive endeavor that requires students to tackle an industry-relevant issue from end-to-end. The process begins with selecting a topic in consultation with faculty mentors, followed by literature review, methodology development, implementation, testing, and presentation.

Project selection is guided by student interests, faculty expertise, and current industry trends. Faculty mentors are assigned based on their research areas and availability to provide guidance throughout the project lifecycle.