Curriculum Overview for Industrial Maintenance Program

The Industrial Maintenance program at Government Polytechnic Bans is structured over 8 semesters to provide a comprehensive educational experience that blends theoretical knowledge with practical application. The curriculum is designed to ensure students are equipped with both foundational and advanced skills required in modern industrial environments.

Detailed Course Descriptions for Advanced Departmental Electives

These advanced elective courses are designed to deepen students' understanding of specialized topics within Industrial Maintenance and prepare them for future research or industry roles.

• Artificial Intelligence in Maintenance: This course explores the application of AI techniques such as neural networks, machine learning, and deep learning in predictive maintenance. Students learn how to build models that can detect anomalies in equipment behavior and predict failures before they occur.
• Industrial IoT & Big Data Analytics: Focuses on the integration of sensors, actuators, and communication protocols in industrial environments. Students gain hands-on experience with platforms like AWS IoT Core and Azure IoT Hub, analyzing real-time data streams for optimization purposes.
• Predictive Maintenance Techniques: Covers statistical methods and algorithms used in predicting equipment failures. The course includes practical sessions on using MATLAB and Python for data analysis and forecasting models.
• Maintenance of Rotating Equipment: Provides in-depth knowledge about turbines, compressors, motors, and pumps. Students study vibration analysis, lubrication systems, and thermal monitoring techniques specific to rotating machinery.
• Sustainable Maintenance Practices: Emphasizes eco-friendly approaches to maintenance, including waste reduction, energy efficiency, and environmental impact assessments. The course also covers green certifications and compliance with global sustainability standards.
• Nuclear & Power Plant Maintenance: Designed for students interested in nuclear or power plant environments, this course covers safety protocols, regulatory compliance, and specialized maintenance practices in high-risk industries.
• Oil & Gas Industry Maintenance: Focuses on the unique challenges faced in upstream and downstream operations. Students learn about pipeline systems, offshore platforms, and drilling equipment maintenance under extreme conditions.
• Maintenance of Process Industries: Covers maintenance practices specific to chemical, pharmaceutical, and food processing industries. The course addresses hygiene standards, contamination control, and quality assurance in process environments.
• Marine & Offshore Maintenance: Prepares students for careers in marine engineering and offshore platforms. Topics include shipyard maintenance, offshore rig operations, and corrosion prevention techniques.
• Industrial Automation & Robotics: Introduces automation technologies such as PLC programming, robotic arms, and SCADA systems. Students engage in lab sessions involving industrial robots and programmable controllers.

Project-Based Learning Philosophy

The department strongly believes that project-based learning is essential for developing practical skills and real-world problem-solving capabilities. From the second year onwards, students are assigned mini-projects that simulate real-life industrial scenarios.

Mini-projects typically involve teams of 3-5 students working under faculty supervision. Each project must have clear objectives, deliverables, and timelines. Projects are evaluated based on technical content, presentation quality, and innovation.

The final-year thesis or capstone project is a significant component of the program. Students select projects based on their interests and career goals, often aligned with industry needs. Faculty mentors guide students through research methodology, data collection, analysis, and documentation.

Project selection process involves a proposal submission where students present their ideas to a panel of faculty members. The evaluation criteria include feasibility, relevance, novelty, and potential impact. Successful projects may lead to publication opportunities or patent applications.