Course Structure Overview
The Industrial Maintenance program is structured over 8 semesters with a carefully balanced mix of theoretical knowledge, practical skills, and real-world application. The curriculum is designed to progressively build upon foundational concepts while introducing students to advanced topics relevant to modern industrial practices.
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| I | IM-101 | Engineering Mathematics I | 3-1-0-4 | - |
| I | IM-102 | Physics for Engineers | 3-1-0-4 | - |
| I | IM-103 | Chemistry for Engineering | 3-1-0-4 | - |
| I | IM-104 | Basic Electrical and Electronics Engineering | 3-1-0-4 | - |
| I | IM-105 | Engineering Mechanics | 3-1-0-4 | - |
| I | IM-106 | Introduction to Industrial Maintenance | 2-1-0-3 | - |
| I | IM-107 | Workshop Practice I | 0-0-4-2 | - |
| II | IM-201 | Engineering Mathematics II | 3-1-0-4 | IM-101 |
| II | IM-202 | Thermodynamics | 3-1-0-4 | IM-102 |
| II | IM-203 | Mechanics of Materials | 3-1-0-4 | IM-105 |
| II | IM-204 | Digital Electronics and Logic Design | 3-1-0-4 | IM-104 |
| II | IM-205 | Mechanical Measurements | 3-1-0-4 | - |
| II | IM-206 | Industrial Safety and Health | 2-1-0-3 | - |
| II | IM-207 | Workshop Practice II | 0-0-4-2 | - |
| III | IM-301 | Machine Design I | 3-1-0-4 | IM-203 |
| III | IM-302 | Control Systems | 3-1-0-4 | IM-201 |
| III | IM-303 | Materials Science and Engineering | 3-1-0-4 | IM-103 |
| III | IM-304 | Process Instrumentation | 3-1-0-4 | IM-204 |
| III | IM-305 | Computer-Aided Design (CAD) | 2-1-0-3 | IM-105 |
| III | IM-306 | Industrial Maintenance Principles | 3-1-0-4 | - |
| IV | IM-401 | Machine Design II | 3-1-0-4 | IM-301 |
| IV | IM-402 | Industrial Automation | 3-1-0-4 | IM-302 |
| IV | IM-403 | Data Analytics for Maintenance | 3-1-0-4 | IM-201 |
| IV | IM-404 | Electrical Power Systems | 3-1-0-4 | IM-104 |
| IV | IM-405 | Maintenance Planning and Scheduling | 2-1-0-3 | - |
| IV | IM-406 | Quality Assurance and Reliability Engineering | 3-1-0-4 | - |
| V | IM-501 | Predictive Maintenance Technologies | 3-1-0-4 | IM-403 |
| V | IM-502 | Advanced Process Control | 3-1-0-4 | IM-302 |
| V | IM-503 | Digital Twin Modeling | 3-1-0-4 | IM-402 |
| V | IM-504 | Robotics and Automation in Industry | 3-1-0-4 | IM-402 |
| V | IM-505 | Energy Systems Maintenance | 3-1-0-4 | - |
| V | IM-506 | Research Methodology | 2-1-0-3 | - |
| VI | IM-601 | Industrial Data Analytics | 3-1-0-4 | IM-403 |
| VI | IM-602 | Process Safety Management | 3-1-0-4 | IM-505 |
| VI | IM-603 | Maintenance Optimization Techniques | 3-1-0-4 | IM-405 |
| VI | IM-604 | Advanced CAD and Simulation | 2-1-0-3 | IM-305 |
| VI | IM-605 | Internship I | 0-0-8-4 | - |
| VII | IM-701 | Smart Manufacturing Systems | 3-1-0-4 | IM-504 |
| VII | IM-702 | Industrial IoT and Sensor Networks | 3-1-0-4 | IM-402 |
| VII | IM-703 | Renewable Energy Systems Maintenance | 3-1-0-4 | IM-505 |
| VII | IM-704 | Chemical Process Equipment Maintenance | 3-1-0-4 | - |
| VII | IM-705 | Maintenance Project Management | 2-1-0-3 | - |
| VIII | IM-801 | Final Year Thesis/Capstone Project | 0-0-16-8 | IM-705 |
| VIII | IM-802 | Internship II | 0-0-12-6 | - |
| VIII | IM-803 | Professional Ethics and Sustainability | 2-1-0-3 | - |
Advanced Departmental Elective Courses
Several advanced departmental elective courses provide specialized knowledge in specific areas of industrial maintenance:
Predictive Maintenance Technologies (IM-501): This course focuses on leveraging data analytics, machine learning, and sensor technologies to predict equipment failures before they occur. Students learn to implement predictive models using tools like Python, MATLAB, and various SCADA platforms.
Advanced Process Control (IM-502): Designed for students interested in automation systems, this course explores advanced control strategies such as model predictive control, adaptive control, and multivariable control systems used in complex industrial environments.
Digital Twin Modeling (IM-503): This course introduces students to the concept of digital twins—virtual replicas of physical assets that simulate real-world behavior. Students learn to create, maintain, and utilize digital twin models for performance optimization and maintenance planning.
Robotics and Automation in Industry (IM-504): A hands-on course covering industrial robotics design, programming, and integration into manufacturing systems. Students work with real robotic arms and automation equipment to develop solutions for industrial challenges.
Energy Systems Maintenance (IM-505): Focuses on the maintenance of power generation systems including thermal, hydroelectric, nuclear, and renewable energy sources. Students gain practical experience in power plant operations and safety protocols.
Maintenance Planning and Scheduling (IM-405): This course teaches students how to plan and schedule maintenance activities effectively using techniques like Critical Path Method (CPM), Gantt charts, and resource allocation strategies.
Industrial Data Analytics (IM-601): Students learn to analyze large volumes of industrial data to identify trends, predict outcomes, and optimize maintenance schedules. The course covers statistical analysis, machine learning algorithms, and big data technologies.
Process Safety Management (IM-602): Emphasizes the importance of safety in industrial environments, covering hazard identification, risk assessment, emergency response planning, and regulatory compliance.
Maintenance Optimization Techniques (IM-603): This course explores various optimization techniques used in maintenance management including cost-benefit analysis, resource allocation models, and performance evaluation metrics.
Smart Manufacturing Systems (IM-701): Introduces students to Industry 4.0 concepts including smart factories, cyber-physical systems, and interconnected manufacturing processes that integrate AI, IoT, and cloud computing technologies.
Industrial IoT and Sensor Networks (IM-702): Focuses on sensor technology integration in industrial environments, covering wireless communication protocols, network topologies, and data transmission methods used in smart maintenance systems.
Renewable Energy Systems Maintenance (IM-703): Provides comprehensive knowledge of maintaining wind turbines, solar panels, hydroelectric generators, and other renewable energy systems with emphasis on environmental sustainability and efficiency optimization.
Chemical Process Equipment Maintenance (IM-704): Covers the specific maintenance requirements for chemical processing equipment including reactors, distillation columns, heat exchangers, and piping systems used in petrochemical industries.
Maintenance Project Management (IM-705): Teaches students how to manage complex maintenance projects from inception to completion, including budgeting, resource allocation, timeline management, and stakeholder communication.
Project-Based Learning Philosophy
Our program strongly emphasizes project-based learning as a core component of education. Projects are designed to bridge the gap between theoretical knowledge and practical application in real industrial environments.
The mandatory mini-projects during the second year involve small-scale simulations or laboratory-based experiments that reinforce classroom learning. These projects are assessed based on technical accuracy, innovation, teamwork, and presentation skills.
During the final year, students undertake a comprehensive capstone project under faculty supervision. The process involves identifying an industry problem, conducting research, developing solutions, and presenting findings to both academic and industry panels.
Students can choose their projects from a list of industry-sponsored topics or propose their own ideas in consultation with faculty members. Each student is assigned a mentor who provides guidance throughout the project lifecycle, ensuring alignment with current industry standards and best practices.