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Advanced Manufacturing and Smart Factories: Hands-On Mini Project Series

Design. Simulate. Predict. Your smart factory starts here.

Skills you will gain:

A 4-day, mentor-led virtual series where you program CNC machining, design robot cells, build a digital twin with IoT data, and train a predictive-maintenance model using Fusion 360, RoboDK, and Python/Jupyter—ending with four portfolio-ready mini projects.

Aim: Enable participants to build an end-to-end smart-factory pipeline—CNC, robotics, digital twins, and predictive maintenance—using Fusion 360, RoboDK, Python/Jupyter, and IoT tools, culminating in four portfolio-ready mini projects.

  • Map the end-to-end smart-factory workflow (CNC → Robotics → Twin → Analytics).

  • Program & simulate CNC toolpaths in Fusion 360.

  • Design & validate a robotic cell in RoboDK (reach, safety, cycle time).

  • Build a basic digital twin with simulated IoT data and compute KPIs (OEE/throughput).

  • Train and interpret a predictive-maintenance model in Python.

  • Create a simple dashboard and package portfolio-ready artifacts.

What you will learn?

📅 Day 1 – CNC Precision Machining Project

  • Overview of CNC Machining in Smart Factories
  • Introduction to G-Code Syntax and Workflow
  • Setting up a simulation environment in Fusion 360
  • Toolpath optimization and error correction techniques
  • Live Demo: Programming a milling path for a precision part
  • 🧩 Mini Project: CNC Precision Machining

📅 Day 2 – Robot Cell Design Project

  • Basics of Industrial and Collaborative Robots (Cobots)
  • Robotic cell design principles (layout, reach, safety zones)
  • Introduction to RoboDK / Visual Components for simulation
  • Live Demo: Building a robotic pick-and-place system
  • 🧩 Mini Project: Robot Cell Design

📅 Day 3 – Digital Twin Simulation Project

  • Introduction to Digital Twin Technology and Industry 4.0 Concepts
  • Data integration with IoT sensors and SCADA interfaces
  • Live Demo: Creating a virtual factory model and simulating live data inputs
  • Visualizing production metrics through dashboards
  • 🧩 Mini Project: Digital Twin Simulation

📅 Day 4 – Predictive Maintenance Analytics

  • Basics of Predictive Maintenance and Industrial Data Analytics
  • Overview of sensor data and machine logs
  • Introduction to Python, Pandas, and Scikit-learn for analytics
  • Live Demo: Building a simple ML model for CNC maintenance prediction
  • 🧩 Mini Project: Predictive Maintenance Model

Mentor Profile

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Intended For :

  • UG/PG students in Mechanical, Manufacturing, Mechatronics, Industrial, EE, or CS.

  • Early-career engineers/technicians in CNC, robotics, automation, or OT.

  • Plant operations, maintenance & reliability engineers; production managers.

  • Data/AI engineers (or aspirants) exploring Industry 4.0 use cases.

  • Faculty/trainers and startup founders building smart-manufacturing solutions.

Career Supporting Skills