Some of the completed and ongoing projects are mentioned below:

1. Hybrid and Smart Manufacturing (Industry 4.0)


Objectives:
  • Design & integration of machining and 3D Printing technologies (Metal and polymers)
  • Design of multi-material, multi-colour nozzle systems for additive manufacturing
  • Repair/Remanufacturing and reverse engineering automation.
  • Knowledge identification, elicitation and capitalization
  • Tool-path generation and optimization
  • Software system development (Simulation close to the reality)
  • Automation of Laser Cladding and repair processes

2. Intelligent Design and topology optimization


Objectives:
  • Design and develop systems to enable Industry 4.0
  • Use the hybrid deposition paths to assist the level set topology optimization process
  • Use the hybrid deposition paths to assist the level set topology optimization process
  • A general topology optimization method for load-bearing 3D printing parts
  • Repair and Remanufacturing modeling

3. Industrial Automation (Robotics)


Objectives:
  • Vision and sensors based approach (2D/3D)
  • Robot-assisted machine-tending process
  • Human-robot collaboration
  • Autonomous repair and manufacturing processes
  • Automated Assembly/Disassembly
  • Multi-robot path planning
Expected results:
  • Path planning and collision avoidance
  • Autonomous processes
  • Real-time planning and re-planning
  • Enhanced productivity

4. Vision assisted collision detection and avoidance in multi-axis CNC machining environment

Objectives:
  • Vision assisted automatic collision detection and avoidance in multi-axis machining environment
  • Intelligent and safe tool-path planning and optimization
  • Intelligent multi-tool synchronization and planning
  • Vision based object detection and identification in manufacturing environment
Expected results:
  • Safe and efficient virtual and real manufacturing
  • Enhanced productivity and quality

5. Zero-defect Manufacturing (vision-assisted inspection)



Objectives:
  • Big-data analysis for quality management and control
  • Construction 4.0: Framing inspection process
  • Food inspection and control
  • Machine Learning and AI
  • Automatic data extraction and analysis from a manufacturing system
Expected results:
  • Higher production quality
  • Data availability for analysis and forcasting
  • Process optimization and Improvement

6. Lean 4.0: Hybrid Lean and ERP Systems


Objectives:
  • Creating joy, excitement and love for learning
  • Enhancing tradiational Lean tools for Industry 4.0
  • To improve throughput of production
  • Efficient tools selection in design process
  • Integrated Hybrid Lean-ERP systems
Expected results:
  • Intelligent planning
  • Better knowledge about machine availability / uptime
  • Bottleneck identification
  • Waste minimization
  • Value stream mapping
  • Process optimization for SMEs and construction companies