M-TECH in Industrial Automation Robotics at Manipal Institute of Technology
Udupi, Karnataka
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About the Specialization
What is Industrial Automation & Robotics at Manipal Institute of Technology Udupi?
This Industrial Automation & Robotics program at Manipal Institute of Technology focuses on equipping students with advanced knowledge in control systems, robotics, and automation technologies crucial for modern manufacturing. India''''s rapidly growing industrial sector, especially in automotive, electronics, and defense, demands skilled professionals to drive smart factories and integrate advanced robotics, making this program highly relevant for shaping the future of Indian industries.
Who Should Apply?
This program is ideal for fresh graduates with a background in engineering disciplines like Mechanical, Mechatronics, Electrical, Electronics, or Instrumentation, seeking entry into high-tech manufacturing and automation roles. It also suits working professionals aiming to upskill in areas like advanced robotics, AI-driven automation, or IIoT, enabling them to lead digital transformation initiatives in their organizations across India.
Why Choose This Course?
Graduates of this program can expect to pursue rewarding India-specific career paths as Automation Engineers, Robotics Engineers, PLC Programmers, Mechatronics Specialists, or R&D Engineers in various sectors. Entry-level salaries typically range from INR 6-10 LPA, with experienced professionals earning INR 15-30 LPA or more. The program aligns with industry certifications in robotics and control systems, fostering significant growth trajectories in Indian companies.
Student Success Practices
Foundation Stage
Master Core Automation & Robotics Fundamentals- (Semester 1-2)
Dedicate significant time to understanding the theoretical underpinnings of advanced control systems, robot kinematics, and industrial automation principles. Actively participate in labs, completing all assignments and experimenting beyond prescribed tasks. Form study groups to discuss complex topics and practice problem-solving.
Tools & Resources
MATLAB/Simulink, Python for robotics (RoPy), PLC simulation software (e.g., Rockwell Studio 5000, Siemens TIA Portal), Online courses (Coursera, NPTEL) on control theory and robotics
Career Connection
A strong foundation in these core areas is critical for understanding and developing complex automated systems, which is a prerequisite for entry-level roles in automation, robotics, and mechatronics engineering.
Develop Proficiency in Programming & Simulation- (Semester 1-2)
Focus on hands-on programming skills essential for automation, including PLC programming (ladder logic, structured text), robot programming (ROS, teach pendant), and simulation tools. Engage in mini-projects to apply theoretical knowledge, such as building simple automated sequences or robot path planning simulations.
Tools & Resources
Robotics Operating System (ROS), Gazebo simulator, Python for AI/ML, Industrial robot simulation software (e.g., ABB RobotStudio, Fanuc ROBOGUIDE), GitHub for version control
Career Connection
Proficiency in programming and simulation tools is highly sought after by employers for roles involving system development, testing, and deployment in industrial environments.
Cultivate Research Acumen & Academic Writing- (Semester 1-2)
Start reading research papers in your areas of interest from the very beginning. Actively participate in research methodology courses, paying attention to literature review techniques and experimental design. Seek opportunities to assist professors with their research projects to gain early exposure to academic rigor and scientific writing.
Tools & Resources
IEEE Xplore, Scopus, Google Scholar for research papers, LaTeX for academic writing, Zotero/Mendeley for citation management
Career Connection
Strong research skills are vital for M.Tech projects, leading to publishable work, and are highly valued in R&D roles, product development, and future doctoral studies.
Intermediate Stage
Dive Deep into Specialization through Electives- (Semester 3)
Strategically choose program electives that align with your career interests (e.g., Vision Systems, Mobile Robotics, IIoT). Go beyond classroom learning by exploring advanced topics in these areas through online courses, workshops, and industry seminars. Aim to implement concepts from electives in small projects or research tasks.
Tools & Resources
OpenCV for vision, NVIDIA Jetson boards for embedded AI, Arduino/Raspberry Pi for IIoT prototypes, Industry-specific software for chosen elective areas
Career Connection
Specializing through electives creates a unique skill set, making you a more attractive candidate for niche roles in advanced robotics, smart manufacturing, or data-driven automation.
Secure & Excel in Industrial Internships- (Semester 3 (or between Semester 2 and 3))
Actively seek and secure internships in relevant industries (manufacturing, automotive, robotics companies) during summer breaks or dedicated internship periods. Focus on practical application of your academic knowledge, hands-on experience with industrial hardware/software, and understanding real-world project cycles.
Tools & Resources
LinkedIn, University placement cells, Industry contacts, Company career portals for internship applications
Career Connection
Internships provide invaluable industry exposure, build professional networks, enhance resume quality, and often lead to pre-placement offers, significantly boosting job prospects.
Network with Industry Professionals & Alumni- (Semester 3)
Attend industry conferences, workshops, and guest lectures to meet professionals and understand current industry trends and challenges. Connect with MIT alumni working in automation and robotics to gain insights, mentorship, and potential career leads. Leverage these connections for project ideas and career guidance.
Tools & Resources
LinkedIn, Professional bodies (e.g., Institution of Engineers India - IEI, Robotics Society of India), Industry events calendars
Career Connection
A strong professional network is crucial for job referrals, mentorship, staying updated on industry demands, and unlocking hidden career opportunities in the Indian market.
Advanced Stage
Execute a High-Impact Master''''s Project- (Semester 4)
For Project Work Phase II, choose a challenging and industry-relevant problem. Dedicate extensive time to research, experimental design, implementation, and rigorous testing. Aim for tangible outcomes, such as a working prototype, a novel algorithm, or a comprehensive simulation study. Seek faculty mentorship and peer feedback regularly.
Tools & Resources
Advanced simulation platforms (e.g., COMSOL, ANSYS, ROS), Industrial-grade hardware (PLCs, robot arms), Specific software for data analysis and visualization
Career Connection
A well-executed master''''s project showcases your ability to solve complex engineering problems, demonstrating practical skills and innovation to potential employers for senior and R&D roles.
Master Interview & Presentation Skills- (Semester 4)
Actively prepare for technical interviews by reviewing core concepts, solving case studies, and practicing common interview questions. Refine your presentation skills for your project defense and potential job interviews. Participate in mock interviews and group discussions organized by the placement cell.
Tools & Resources
Interview preparation platforms (e.g., LeetCode, HackerRank for logic; specific technical interview prep for robotics/automation), University career services, Peer mock interviews
Career Connection
Excellent interview and presentation skills are paramount for converting academic achievements into successful placements in competitive Indian and multinational companies.
Develop Leadership & Teamwork through Collaborations- (Semester 4)
Engage in collaborative projects, either within the university or with industry partners, taking on leadership roles. Learn to manage project timelines, delegate tasks, and effectively communicate technical ideas within a team. This also includes guiding junior students or participating in departmental activities.
Tools & Resources
Project management software (e.g., Trello, Asana), Communication platforms (Microsoft Teams, Slack), Collaborative document editing
Career Connection
Employers highly value candidates who can work effectively in teams and lead projects, which are essential skills for career progression into managerial or senior engineering roles in industry.
Program Structure and Curriculum
Eligibility:
- A pass in Bachelor’s degree or equivalent in relevant discipline with not less than 50% aggregate marks. Relevant disciplines include B.Tech./B.E. in Mechatronics, Industrial Automation, Manufacturing Engineering, Mechanical Engineering, Automobile Engineering, Production Engineering, Industrial Engineering, Electronics & Communication Engineering (ECE), Electrical & Electronics Engineering (EEE), Instrumentation & Control Engineering, etc.
Duration: 4 semesters / 2 years
Credits: 80 Credits
Assessment: Internal: 50% (for theory), 60% (for practical/lab), 50% (for project), External: 50% (for theory), 40% (for practical/lab), 50% (for project)
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MTR 6101 | Advanced Concepts in Control Systems | Core | 4 | Review of Linear Control Systems, State-Space Analysis, Optimal Control Theory, Adaptive Control Strategies, Robust Control Design, Non-linear Control Systems |
| MTR 6102 | Advanced Robotics | Core | 4 | Robot Kinematics (Forward and Inverse), Robot Dynamics (Euler-Lagrange), Trajectory Planning Methods, Robot Control (Force, Impedance), Robot Sensing and Vision Systems, Advanced Manipulators and Parallel Robots |
| MTR 6103 | Industrial Automation | Core | 4 | Automation Concepts and Architectures, PLC Programming (Ladder, Function Block), SCADA and Distributed Control Systems (DCS), Industrial Communication Protocols, Human Machine Interface (HMI) Design, Batch and Continuous Process Control |
| MTR 6104 | Advanced Sensor Technology | Core | 4 | Principles of Measurement and Instrumentation, Smart Sensors and Actuators, MEMS Technology, Optical and Vision Sensors, Sensor Networks and Data Acquisition, Transducers and Signal Conditioning |
| MTR 6105 | Advanced Control Systems Lab | Lab | 2 | MATLAB/Simulink for Control System Design, PLC Programming and Interfacing, SCADA System Implementation, Industrial Controllers and Tuners, System Identification and Parameter Estimation, Real-time Control Applications |
| MTR 6106 | Advanced Robotics Lab | Lab | 2 | Robot Programming (Teach Pendant, Offline), Robot Vision Applications, Manipulator Control and Trajectory Generation, Robot Simulation and Modeling, Industrial Robot Operation and Safety, End-effector Design and Gripping Mechanisms |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MTR 6201 | Artificial Intelligence and Machine Learning for Automation | Core | 4 | AI Concepts and Problem Solving, Machine Learning Algorithms (Supervised, Unsupervised), Deep Learning Basics, Reinforcement Learning Fundamentals, Applications in Industrial Automation, Data-driven Control and Optimization |
| MTR 6202 | Advanced Manufacturing Systems | Core | 4 | Computer Integrated Manufacturing (CIM), Flexible Manufacturing Systems (FMS), Lean and Agile Manufacturing, Additive Manufacturing Processes, Advanced Machining Techniques, Production Planning and Scheduling |
| MTR 6203 | Modelling and Simulation of Dynamic Systems | Core | 4 | System Dynamics Principles, Mathematical Modeling (Mechanical, Electrical, Fluid), Bond Graph Modeling, Numerical Methods for Simulation, Simulation Software (MATLAB/Simulink, ADAMS), Validation and Verification of Models |
| MTR 6204 | Research Methodology | Core | 3 | Formulation of Research Problem, Literature Review Techniques, Experimental Design and Data Collection, Statistical Analysis and Interpretation, Technical Report Writing, Ethics and Plagiarism in Research |
| MTR 6205 | AI and ML for Automation Lab | Lab | 2 | Python/R for Machine Learning Implementations, Vision-based Automation Projects, Robotic Learning Tasks, Predictive Maintenance Applications, Optimization Algorithms for Industrial Processes, Data Preprocessing and Feature Engineering |
| MTR 6206 | Advanced Manufacturing Lab | Lab | 2 | CNC Programming and Machining, Computer-Aided Manufacturing (CAM), Rapid Prototyping Techniques, Metrology and Quality Inspection, Automation Cells Design and Setup, Process Optimization and Simulation |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MTR 7111 | Vision Systems for Automation | Elective (Program Elective 1, 2, or 3 option) | 3 | Image Acquisition and Sensing, Image Processing Techniques, Feature Extraction and Segmentation, Object Recognition and Tracking, 3D Vision and Stereo Vision, Applications in Robotics and Quality Inspection |
| MTR 7112 | Mobile Robotics | Elective (Program Elective 1, 2, or 3 option) | 3 | Mobile Robot Locomotion and Kinematics, Localization and Mapping (SLAM), Path Planning and Navigation, Obstacle Avoidance Strategies, Multi-Robot Systems, Human-Robot Interaction for Mobile Platforms |
| MTR 7113 | Additive Manufacturing | Elective (Program Elective 1, 2, or 3 option) | 3 | Principles of Additive Manufacturing, Materials for AM Processes, Specific AM Processes (FDM, SLA, SLS, EBM), Design for Additive Manufacturing, Post-processing and Finishing, Applications and Challenges of AM |
| MTR 7114 | Industrial Internet of Things (IIoT) | Elective (Program Elective 1, 2, or 3 option) | 3 | IIoT Architecture and Components, Sensors, Actuators, and Gateways for IIoT, Edge and Cloud Computing in IIoT, Big Data Analytics for Industrial Data, Cyber-Physical Systems (CPS), Security and Privacy in IIoT |
| MTR 7115 | Data Analytics for Industrial Applications | Elective (Program Elective 1, 2, or 3 option) | 3 | Data Collection and Preprocessing, Statistical Analysis for Industrial Data, Predictive Modeling and Forecasting, Optimization Techniques in Industry, Anomaly Detection and Diagnosis, Maintenance Analytics and Quality Control |
| MTR 7116 | Quality Control and Reliability Engineering | Elective (Program Elective 1, 2, or 3 option) | 3 | Statistical Quality Control (SQC), Control Charts (Variable and Attribute), Acceptance Sampling, Reliability Concepts and Metrics, Failure Analysis and Maintainability, Six Sigma Methodologies |
| MTR 7150 | Project Work Phase – I | Project | 8 | Problem Identification and Scoping, Comprehensive Literature Survey, Methodology Development, Preliminary Design and Simulation, Data Collection Planning, Report Writing and Presentation |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MTR 7250 | Project Work Phase – II | Project | 18 | Detailed Design and Implementation, Experimental Setup and Validation, Data Analysis and Interpretation, Results Discussion and Conclusion, Thesis Writing and Documentation, Presentation and Viva-Voce Examination |