Semester-wise syllabus for an M.Tech in Industrial Automation

 

Semester 1:

 Core Foundations 

1. Industrial Control Systems 

   - PLC programming (Ladder Logic, Structured Text), PID control, and SCADA systems. 

2. Sensors and Actuators 

   - Types (proximity, pressure, vision sensors), signal conditioning, and actuator mechanisms (pneumatic, hydraulic). 

3. Industrial Communication Protocols 

   - Fieldbus (PROFIBUS, Modbus), Ethernet/IP, OPC-UA, and IoT protocols (MQTT, CoAP). 

4. Advanced Process Control 

   - Model predictive control (MPC), adaptive control, and multivariable control systems. 

5. Lab Work

   - PLC programming (Siemens/Allen-Bradley), sensor-actuator integration, HMI design. 

 

Semester 2:

Advanced Automation & Robotics 

1. Industrial Robotics 

   - Robot kinematics/dynamics, programming (ABB/KUKA), collaborative robots (Cobots), and vision-guided systems. 

2. Automation in Manufacturing 

   - CNC machines, conveyor systems, automated guided vehicles (AGVs), and lean manufacturing principles. 

3. Process Instrumentation 

   - Flow, level, temperature, and pressure measurement systems, calibration, and smart transmitters. 

4. Elective 1 

   - Options: AI in Automation, Digital Twins, Smart Grid Integration. 

5. Lab Work 

   - Robotic welding/picking simulations (ROS), AGV programming, digital twin modeling (MATLAB/Simulink). 

 

Semester 3:

Industry 4.0 & Emerging Technologies 

1. Industrial IoT (IIoT) and Cyber-Physical Systems 

   - Edge computing, predictive maintenance, cloud integration (AWS IoT, Azure), and cybersecurity for OT/IT convergence. 

2. Machine Learning for Automation 

   - Anomaly detection, predictive analytics, and AI-driven optimization in production lines. 

3. Elective 2 

   - Options: Additive Manufacturing, Energy Management Systems, Autonomous Systems. 

4. Elective 3 

   - Options: Human-Machine Interface (HMI) Design, Advanced Motion Control, Industrial Cybersecurity. 

5. Research Project (Phase 1) 

   - Proposal (e.g., AI-based quality control, digital twin for a smart factory, or energy-efficient automation). 

6. Lab Work 

   - IIoT sensor networks, AI-driven defect detection (Python/OpenCV), additive manufacturing (3D printing). 

 

Semester 4:

Dissertation & Industry Integration 

1. Dissertation/Thesis 

   - Focus areas: Smart factory implementation, robotic process automation (RPA), sustainable automation, or AI-optimized production. 

2. Industry Internship (Optional) 

   - Collaborations with automotive (Tesla, Tata Motors), FMCG (Unilever), or automation giants (Siemens, Rockwell). 

3. Emerging Trends Seminar 

   - Topics: Digital twins, swarm robotics, blockchain for supply chain automation, and green manufacturing. 

4. Seminar & Viva Voce 

   - Presentation and defense of research, peer reviews, and industry expert feedback. 

 

Electives (Across Semesters 2–3) 

- Digital Twins: Virtual commissioning, real-time simulation, and predictive analytics. 

- Smart Grid Integration: Energy-efficient automation, demand-side management, and microgrids. 

- Additive Manufacturing: Industrial 3D printing, topology optimization, and rapid prototyping. 

- Industrial Cybersecurity: OT security, intrusion detection, and secure PLC programming. 

 

Tools & Technologies 

- PLC/SCADA: Siemens TIA Portal, Rockwell Studio 5000, Ignition SCADA. 

- Simulation: MATLAB/Simulink, Digital Twin software (ANSYS Twin Builder), RobotStudio. 

- AI/ML: Python (TensorFlow, PyTorch), edge AI platforms (NVIDIA Jetson). 

- IoT: Node-RED, AWS IoT Core, Raspberry Pi/Arduino for prototyping. 

- CAD/CAM: AutoCAD, SolidWorks, Fusion 360. 

 

Industry Applications 

- Automotive: Robotic assembly lines, EV battery manufacturing. 

- Pharmaceuticals: Automated packaging, sterile process automation. 

- Oil & Gas: Pipeline monitoring, remote operation centers (ROCs). 

- Food & Beverage: Automated bottling, quality inspection using vision systems. 

- Aerospace: Precision machining, composite material handling.