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2-Month Hybrid Fellowship
Final Year B. Tech Students
12th April 2026
15th April 2026
About the Fellowship Programme
A structured, three-phase hybrid fellowship programme designed to take final year B.Tech students from foundational exposure to live project deployment inside an actual smart factory environment.
Online Component:
Concept building and guided challenges through expert-led virtual sessions.
On-Campus Component:
Hands-on project deployment on NAMTECH’s Industry 4.0 factory floor, working with live machines and real production data.
Why This Fellowship is Different?
Not Just Another Internship. A Launchpad into the Future of Manufacturing.
Live Factory
Access
Work on NAMTECH's operational Industry 4.0 mini factories.
AI and Manufacturing Integration
Deploy ML models on real sensor data from live production lines, not textbook datasets.
Digital Twin
Projects
Build and simulate digital replicas of real manufacturing cells used in industry.
Expert
Mentorship
Guidance from faculty with IIT and international background, plus professionals from global MNCs.
Industry Case
Studiess
Solve real challenges sourced from ArcelorMittal Nippon Steel India's production ecosystem.
Fellowship
Credentials
Receive a Certificate, Letter of Recommendation, and a real project to show.
Programme Overview
Phases 
Programme Benefits 
Eligibility 
Shortlisting Criteria Phase 1: April 2026 (Online)
A curated introduction to the intelligence behind modern manufacturing with expert-led sessions paired with guided mini-challenges that give you a real taste of what is possible. Designed to spark curiosity The rest unfolds on campus.
| MODULE & WHAT YOU EXPLORE | GUIDED MINI-CHALLENGE |
|---|---|
| The Smart Factory DecodedHow Industry 4.0 is rewriting the rules of production; cyber-physical systems; real factory architecture from NAMTECH’s floor. | Mini-ChallengeSketch a data flow map for one manufacturing process identify where intelligence can be added and where it is missing. |
| AI & Data on the Factory FloorHow machines generate data, what patterns mean, and how AI turns noise into actionable manufacturing decisions. | Mini-ChallengeGiven a sample sensor dataset, complete a guided Python snippet to identify anomalies scaffold provided, you supply the logic. |
| Seeing What Machines SeeIntroduction to computer vision in quality inspection and how a camera replaces manual inspection at scale. | Mini-ChallengeRun a pre-built defect detection script on sample images. Tweak one parameter and observe how detection accuracy shifts. |
| Your Factory’s Digital TwinWhat a digital twin is, why global manufacturers are racing to build them, and what it really takes to create one. | Mini-ChallengeIn a simplified simulation environment, modify one variable in a virtual conveyor model and document how the system responds. |
| The Connected FactoryIIoT basics, sensor-to-cloud pipelines, and how real-time data powers smarter manufacturing decisions. | Mini-ChallengeTrace a live data stream from sensor to dashboard in a guided environment. Identify and explain the bottleneck in the pipeline. |
| Additive Manufacturing & Smart ProductionAdditive manufacturing is transforming production through design freedom, efficiency, and digital integration in Industry 4.0. | Mini-ChallengeDesign and fabricate a component using AM, selecting and optimizing process parameters to reduce defects and enhance performance. |
Phase 2: May 2026 (Online)
Expert-led seminars, industry masterclasses, live case studies from the manufacturing floor, and guided project formulation the bridge between knowledge and execution.
| Week 1 Industry MasterclassGlobal and Indian manufacturing leaders share live factory insights, career pathways, and in demand skills.. | Week 2 Research SeminarFaculty experts and external researchers present cutting-edge work in digital twins, AI quality control, and sustainable production. |
| Week 3 Project FloatingCurated real-world projects are unveiled. Students review briefs, assess feasibility, and align before team formation begins. | Week 4 Design ChallengeTeams present solution architecture to faculty mentors for review and finalization before the on-campus phase begins. |
Phase 3: June 2026 (Two weeks, On-Campus)
Full-time, immersive project execution on NAMTECH’s smart manufacturing campus. Students work alongside faculty mentors, using industry-grade equipment from Festo, Schneider, Siemens, to build, test, and demonstrate real solutions.
| Sample Project Themes (Full project list revealed to shortlisted candidates only) | |
|---|---|
| AI-Based Visual Quality Inspection System | Digital Twin for a Live Factory |
| Predictive Maintenance for Industrial Robots | Smart Energy Monitoring & Optimization Platform |
| IIoT Real-Time Production Dashboard | AI-Driven Adaptive Scheduling for Smart Assembly |
Fellowship Programme Benefits
- Build and deploy projects on live Industry 4.0 factory equipment.
- Project funding support for approved hardware and development expenses.
- Free access to the Phase 1 online Smart Manufacturing & AI course.
- Webinars, industry masterclasses, and expert talks fully sponsored by NAMTECH.
- Direct exposure to ArcelorMittal Nippon Steel India’s real manufacturing challenges.
- Academic mentoring by international Academic experts and Industry professionals.
- On-campus accommodation (subject to availability, at actual fees).
- Fellowship Certificate and Letter of Recommendation upon successful completion.
- Access to NAMTECH&’s world-class Smart Manufacturing Labs.
- Gain real-world industry exposure in Automation.
Eligibility
Currently pursuing B.Tech (4th Year, 8th Semester) in Mechanical, Production, Industrial, Manufacturing, Electrical, Electronics, or Computer Science Engineering from any recognized institution/university. Minimum 6.0 CGPA / 60% marks with no active backlogs.
Application Process
STEP 1
Submit online application via Microsoft Forms..
STEP 2
Upload scanned Student ID and latest semester marksheet.
STEP 3
Write a Statement of Interest (max 200 words)
STEP 4
List projects, research, papers, or internships completed to date, with your latest resume.
Shortlisting Criteria
Candidates will be shortlisted based on the following weightage:
50%
Academic Performance
30%
Projects / Research / Internships
20%
Statement of Interest
Faculty
Expert seminars, industry talks, applied case studies, project floating, and guided group discussions for project formulation.
