Curriculum
The curriculum for the B.Tech Process Instrumentation program at School of Instrumentation, Devi Ahilya Vishwavidyalaya is meticulously designed to provide students with a comprehensive understanding of both theoretical principles and practical applications in the field of process instrumentation. The program spans eight semesters over four academic years, ensuring a balanced progression from foundational sciences to specialized engineering concepts.
Semester-wise Course Structure
| Semester | Course Code | Course Title | Credit (L-T-P-C) | Pre-requisites |
|---|---|---|---|---|
| 1st Semester | PH101 | Physics for Engineers | 3-1-0-4 | - |
| 1st Semester | CH101 | Chemistry for Engineers | 3-1-0-4 | - |
| 1st Semester | MA101 | Mathematics I | 4-0-0-4 | - |
| 1st Semester | EE101 | Basic Electrical Engineering | 3-1-0-4 | - |
| 1st Semester | ME101 | Engineering Graphics and Workshop | 2-2-0-3 | - |
| 1st Semester | CS101 | Introduction to Computer Programming | 2-0-2-3 | - |
| 1st Semester | HS101 | English Communication Skills | 2-0-0-2 | - |
| 1st Semester | GE101 | General Education | 2-0-0-2 | - |
| 2nd Semester | PH102 | Physics II | 3-1-0-4 | PH101 |
| 2nd Semester | CH102 | Chemistry II | 3-1-0-4 | CH101 |
| 2nd Semester | MA102 | Mathematics II | 4-0-0-4 | MA101 |
| 2nd Semester | EE102 | Electronics Circuits and Devices | 3-1-0-4 | EE101 |
| 2nd Semester | ME102 | Engineering Mechanics | 3-1-0-4 | - |
| 2nd Semester | CS102 | Data Structures and Algorithms | 3-0-2-5 | CS101 |
| 2nd Semester | HS102 | Communication Skills II | 2-0-0-2 | HS101 |
| 3rd Semester | PH201 | Physics III | 3-1-0-4 | PH102 |
| 3rd Semester | CH201 | Chemistry III | 3-1-0-4 | CH102 |
| 3rd Semester | MA201 | Mathematics III | 4-0-0-4 | MA102 |
| 3rd Semester | EE201 | Digital Electronics and Logic Design | 3-1-0-4 | EE102 |
| 3rd Semester | ME201 | Mechanics of Materials | 3-1-0-4 | ME102 |
| 3rd Semester | CS201 | Object-Oriented Programming in C++ | 2-0-2-4 | CS102 |
| 3rd Semester | IN101 | Introduction to Instrumentation | 3-1-0-4 | - |
| 4th Semester | PH202 | Physics IV | 3-1-0-4 | PH201 |
| 4th Semester | CH202 | Chemistry IV | 3-1-0-4 | CH201 |
| 4th Semester | MA202 | Mathematics IV | 4-0-0-4 | MA201 |
| 4th Semester | EE202 | Signals and Systems | 3-1-0-4 | EE201 |
| 4th Semester | ME202 | Thermodynamics and Heat Transfer | 3-1-0-4 | ME201 |
| 4th Semester | CS202 | Database Management Systems | 3-0-2-5 | CS201 |
| 4th Semester | IN201 | Process Dynamics and Control | 3-1-0-4 | IN101 |
| 5th Semester | PH301 | Physics V | 3-1-0-4 | PH202 |
| 5th Semester | CH301 | Chemistry V | 3-1-0-4 | CH202 |
| 5th Semester | MA301 | Mathematics V | 4-0-0-4 | MA202 |
| 5th Semester | EE301 | Electrical Machines and Drives | 3-1-0-4 | EE202 |
| 5th Semester | ME301 | Fluid Mechanics and Hydraulic Machines | 3-1-0-4 | ME202 |
| 5th Semester | CS301 | Computer Networks | 3-0-2-5 | CS202 |
| 5th Semester | IN301 | Instrumentation Electronics | 3-1-0-4 | IN201 |
| 5th Semester | IN302 | Process Control Systems | 3-1-0-4 | IN201 |
| 6th Semester | PH302 | Physics VI | 3-1-0-4 | PH301 |
| 6th Semester | CH302 | Chemistry VI | 3-1-0-4 | CH301 |
| 6th Semester | MA302 | Mathematics VI | 4-0-0-4 | MA301 |
| 6th Semester | EE302 | Power Electronics and Drives | 3-1-0-4 | EE301 |
| 6th Semester | ME302 | Mechanical Vibrations and Acoustics | 3-1-0-4 | ME301 |
| 6th Semester | CS302 | Software Engineering and Project Management | 3-0-2-5 | CS301 |
| 6th Semester | IN401 | Industrial Automation and PLC Programming | 3-1-0-4 | IN302 |
| 6th Semester | IN402 | Data Acquisition and Signal Processing | 3-1-0-4 | IN301 |
| 7th Semester | PH401 | Physics VII | 3-1-0-4 | PH302 |
| 7th Semester | CH401 | Chemistry VII | 3-1-0-4 | CH302 |
| 7th Semester | MA401 | Mathematics VII | 4-0-0-4 | MA302 |
| 7th Semester | EE401 | Control Systems Design | 3-1-0-4 | EE302 |
| 7th Semester | ME401 | Manufacturing Technology | 3-1-0-4 | ME302 |
| 7th Semester | CS401 | Artificial Intelligence and Machine Learning | 3-0-2-5 | CS302 |
| 7th Semester | IN501 | Advanced Process Modeling and Simulation | 3-1-0-4 | IN401 |
| 7th Semester | IN502 | Cybersecurity for Industrial Systems | 3-1-0-4 | IN402 |
| 8th Semester | PH402 | Physics VIII | 3-1-0-4 | PH401 |
| 8th Semester | CH402 | Chemistry VIII | 3-1-0-4 | CH401 |
| 8th Semester | MA402 | Mathematics VIII | 4-0-0-4 | MA401 |
| 8th Semester | EE402 | Modern Control Theory and Optimization Techniques | 3-1-0-4 | EE401 |
| 8th Semester | ME402 | Energy Systems and Renewable Technologies | 3-1-0-4 | ME401 |
| 8th Semester | CS402 | Internet of Things (IoT) and Cloud Computing | 3-0-2-5 | CS401 |
| 8th Semester | IN601 | Capstone Project - Final Year Thesis | 3-0-0-9 | IN502 |
Advanced Departmental Elective Courses
The department offers a wide array of advanced departmental elective courses designed to deepen students' understanding and enhance their specialization skills:
- Advanced Process Modeling and Simulation: This course explores mathematical modeling techniques, simulation software tools, and optimization methods for complex industrial processes. Students learn how to build dynamic models of real-world systems and validate them against experimental data.
- Cybersecurity for Industrial Systems: Addressing the growing need for secure control systems, this course covers network security protocols, threat analysis, intrusion detection systems, and compliance with international standards such as NIST SP 800-82.
- Data Analytics for Process Optimization: Focused on extracting insights from operational data, this course introduces students to statistical methods, machine learning algorithms, and visualization tools for improving process efficiency and reducing variability.
- Renewable Energy Integration: This course examines the integration of renewable energy sources into existing industrial processes. Topics include solar thermal systems, wind power generation, energy storage solutions, and hybrid systems design.
- Smart Sensors and IoT Integration: Students explore the development and deployment of wireless sensor networks, embedded systems, and Internet of Things (IoT) solutions in industrial environments. Practical sessions involve programming microcontrollers and designing sensor-based applications.
- Process Safety and Risk Management: This course emphasizes the identification, assessment, and mitigation of hazards in industrial operations. Students learn risk analysis methodologies, safety management systems, and regulatory frameworks for ensuring compliance with international standards.
- Energy Efficiency and Sustainability: Covering energy conservation techniques, environmental impact assessments, and sustainable practices in industrial processes, this course provides students with tools to optimize resource utilization while minimizing ecological footprint.
- Industrial Automation and Control Systems: Designed to equip students with skills in designing and implementing automated control systems for manufacturing environments. Students gain hands-on experience with PLCs, SCADA systems, and HMI interfaces.
- Artificial Intelligence in Process Control: This course explores the application of AI techniques such as neural networks, fuzzy logic, and genetic algorithms in process control and optimization. Practical projects include developing intelligent control systems for chemical plants and power generation units.
- Advanced Signal Processing Techniques: Focuses on advanced signal processing methods including wavelet transforms, spectral estimation, and adaptive filtering. Applications in industrial monitoring, diagnostics, and data acquisition are emphasized.
Project-Based Learning Philosophy
The department places significant emphasis on project-based learning as a cornerstone of the educational experience. The philosophy behind this approach is rooted in fostering critical thinking, problem-solving abilities, and practical application skills essential for real-world engineering challenges.
Projects are structured across multiple levels:
- Mini Projects (First Year): These are introductory-level projects that allow students to apply fundamental concepts learned in class to solve simple problems. Mini-projects typically last 4-6 weeks and require a team of 3-5 students.
- Major Projects (Second Year): Students engage in more complex projects involving system design, implementation, and testing. These projects span 8-10 weeks and often involve collaboration with industry partners or faculty research initiatives.
- Final Year Thesis/Capstone Project: The capstone project represents the culmination of the student's academic journey. It involves extensive research, independent study, and innovation in a specialized area within process instrumentation. Students work closely with a faculty advisor and are expected to deliver a comprehensive report and presentation.
The evaluation criteria for these projects are rigorous and multi-faceted:
- Technical Proficiency: Assessment of the technical correctness, depth of understanding, and innovative approach applied to the project.
- Documentation Quality: Evaluation of written reports, diagrams, data analysis, and overall clarity of communication.
- Presentation Skills: Grading based on oral presentations, visual aids, and ability to articulate ideas effectively.
- Team Collaboration: Assessment of teamwork, contribution levels, and coordination among group members.
- Project Execution: Evaluation of project completion status, adherence to timelines, and resolution of unexpected challenges.
Students select projects based on their interests and career aspirations, guided by faculty advisors who provide mentorship throughout the process. The department encourages students to propose innovative ideas or work on real-world problems identified by industry partners or research laboratories.