Course Structure Overview
The Industrial Automation program at School of Instrumentation Devi Ahilya Vishwavidyalaya is structured over eight semesters, providing students with a comprehensive understanding of both theoretical and practical aspects of automation systems. The curriculum includes core engineering subjects, departmental electives, science electives, and laboratory components designed to foster deep learning and skill development.
| Semester | Course Code | Course Title | Credit (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | PHYS101 | Physics for Engineers | 3-1-0-4 | - |
| 1 | MATH101 | Mathematics I | 4-0-0-4 | - |
| 1 | CE101 | Introduction to Engineering | 2-0-0-2 | - |
| 1 | CSE101 | Computer Programming | 3-1-0-4 | - |
| 1 | ENGL101 | English Communication Skills | 2-0-0-2 | - |
| 2 | MATH201 | Mathematics II | 4-0-0-4 | MATH101 |
| 2 | ELEC201 | Electrical Circuits and Networks | 3-1-0-4 | - |
| 2 | PHYS201 | Applied Physics Laboratory | 0-0-3-1 | - |
| 2 | CSE201 | Data Structures and Algorithms | 3-1-0-4 | CSE101 |
| 2 | CHME201 | Chemistry for Engineers | 3-0-0-3 | - |
| 3 | MATH301 | Mathematics III | 4-0-0-4 | MATH201 |
| 3 | ELEC301 | Electromagnetic Fields and Waves | 3-1-0-4 | ELEC201 |
| 3 | CSE301 | Object-Oriented Programming with C++ | 3-1-0-4 | CSE201 |
| 3 | MECH301 | Mechanics of Materials | 3-1-0-4 | - |
| 3 | PROG301 | Probability and Statistics for Engineers | 3-0-0-3 | MATH201 |
| 4 | ELEC401 | Signals and Systems | 3-1-0-4 | ELEC301 |
| 4 | CSE401 | Database Management Systems | 3-1-0-4 | CSE301 |
| 4 | MECH401 | Thermodynamics and Heat Transfer | 3-1-0-4 | - |
| 4 | PROG401 | Control Systems Engineering | 3-1-0-4 | MECH301 |
| 5 | ELEC501 | Microprocessors and Microcontrollers | 3-1-0-4 | ELEC401 |
| 5 | CSE501 | Computer Networks | 3-1-0-4 | CSE401 |
| 5 | MECH501 | Mechanical Design and Drafting | 3-1-0-4 | MECH301 |
| 5 | PROG501 | Digital Signal Processing | 3-1-0-4 | ELEC401 |
| 6 | ELEC601 | Industrial Electronics and Power Systems | 3-1-0-4 | ELEC501 |
| 6 | CSE601 | Software Engineering | 3-1-0-4 | CSE501 |
| 6 | MECH601 | Manufacturing Technology | 3-1-0-4 | MECH501 |
| 6 | PROG601 | Advanced Control Systems | 3-1-0-4 | PROG401 |
| 7 | ELEC701 | Industrial Automation and PLC Programming | 3-1-0-4 | ELEC601 |
| 7 | CSE701 | Artificial Intelligence and Machine Learning | 3-1-0-4 | CSE601 |
| 7 | MECH701 | Automation in Manufacturing Systems | 3-1-0-4 | MECH601 |
| 7 | PROG701 | Robotics and Mechatronics | 3-1-0-4 | PROG601 |
| 8 | ELEC801 | Advanced Automation Technologies | 3-1-0-4 | ELEC701 |
| 8 | CSE801 | Internet of Things (IoT) and Cybersecurity | 3-1-0-4 | CSE701 |
| 8 | MECH801 | Energy Management and Smart Grids | 3-1-0-4 | MECH701 |
| 8 | PROG801 | Capstone Project Development | 0-0-6-3 | PROG701 |
The department's philosophy on project-based learning emphasizes experiential education as a critical component of the curriculum. Students engage in both individual and group projects throughout their academic journey, beginning with foundational mini-projects in early semesters to more complex capstone initiatives in the final year.
Mini-projects are introduced starting from the second semester and involve small-scale applications such as designing simple control systems or simulating basic automation scenarios. These projects aim to reinforce theoretical concepts through practical implementation, encouraging students to apply learned principles in tangible ways.
The final-year thesis/capstone project is a comprehensive endeavor that requires students to select an area of interest within industrial automation and develop a complete solution or innovation. Projects are typically chosen in consultation with faculty mentors based on student interests, current industry trends, and research opportunities available within the department.
Advanced Departmental Electives
Several advanced elective courses are offered to deepen students' expertise in specialized areas of industrial automation:
- Industrial Electronics and Power Systems (ELEC601): This course covers power electronics components, power converters, and their applications in industrial settings. Students gain hands-on experience with various power control devices used in modern manufacturing environments.
- Artificial Intelligence and Machine Learning (CSE701): Designed to introduce students to AI techniques applied in automation systems, including neural networks, deep learning, and reinforcement learning algorithms. Practical sessions involve building models using Python-based libraries like TensorFlow and PyTorch.
- Internet of Things (IoT) and Cybersecurity (CSE801): Focuses on IoT architectures, communication protocols, and security challenges in interconnected industrial systems. Students learn to secure smart devices and networks against potential threats while maintaining operational efficiency.
- Automation in Manufacturing Systems (MECH701): Provides insights into integrating automation technologies into production lines, covering topics such as robotic assembly, conveyor systems, and quality control mechanisms.
- Advanced Control Systems (PROG601): Builds upon earlier control theory knowledge by exploring advanced modeling techniques, robust control strategies, and optimal control methods used in industrial applications.
These elective courses are designed to allow students to tailor their education according to their career goals and emerging technological trends. Each course includes both theoretical lectures and laboratory sessions that enable students to experiment with real-world scenarios.
Project Evaluation Criteria
Projects undertaken during the program are evaluated using a multi-criteria framework:
- Technical Execution: The accuracy of implementation, adherence to design specifications, and use of appropriate tools and techniques.
- Innovation: Originality in problem-solving approaches and incorporation of novel ideas or technologies.
- Documentation: Clarity and completeness of project reports, including diagrams, flowcharts, and results analysis.
- Presentation: Quality of oral presentations and ability to communicate technical concepts effectively.
- Team Collaboration: Effectiveness in working within teams, sharing responsibilities, and contributing meaningfully to collective outcomes.
The evaluation process ensures that students not only acquire technical skills but also develop essential soft skills such as teamwork, time management, and critical thinking.