Research and Development

The Supply Chain Management Cluster adopts the key elements in Industry 4.0 to provide holistic supply chain solutions, looking into how to integrate the processes vertically in the organization, as well as to connect the various stakeholders across the ecosystem, in order to ensure that information is shared and communicated at all the stages of the product flow.

Through this approach, the Supply Chain Management Cluster hopes to support and grow local enterprises to venture into the region using the Supply Chain 4.0 methodologies, derived from the elements in Industry 4.0.

Focus Areas:

  • Warehouse Optimization
    • Warehouse Process Analysis
    • Automating Inventory Management
    • Optimization of Warehouse Resources
  • Transport Optimization
    • Advanced Planning & Optimization in Transportation
    • Prediction of Last-Mile Logistics
  • Back Office Optimization
    • Improve resource utilization/allocation using AI
    • Document Automation
    • Automating the process of Sales/ Services enquiries
  • Supporting the Food Supply Chain
    • Design of Experiments (DOE) to monitor factors affecting crop yield
    • Robotics & automation in farms for internal transport & picking
    • Location & condition control (e.g. cold chain management)
    • Transport planning of deliverables
    • Predictive analytics in demand planning
  • Supporting the Healthcare Supply Chain
    • Early warning system for supply chain risks and deviation
    • Real-time tracking of consumables supplies
    • Inventory tracking
    • Order picking efficiency

 

Some of our projects include:

  • Using AI in Chatbot for Freight Forwarding Companies
    • This project focuses on a Chatbot that can be deployed by Freight Forwarding companies to allow their customer service agents as well as customers to search for HS Codes and INCOTERMS that are critical information for any export shipment. Through Machine Learning, information such as product search frequencies and customer preferences can be captured and analyzed.
  • Visual Container Tracking
    • This project uses Computer Vision and other location sensors to track the movement of vehicles within an indoor facility. The digital information captured allows for real-time data sharing without human intervention, and can be used for further analysis such as prediction of container stay-time.
  • Estimated Time of Completion Prediction for Last-Mile Logistics
    • This project uses Machine Learning algorithms to make forecasts for the ETA and ETD of delivery vehicles, which is crucial for businesses that are in the last-mile logistics area.
  • Deep Learning for Warehouse Process Analysis
    • This project uses Video Analytics to capture activities carried out by personnel doing packing of goods in a warehouse. Through Deep Learning, information such as Time Motion Study and Waste Identification using LEAN methodologies can be identified to improve the process.
  • Inventory Detection using Computer Vision
    • This project uses Computer Vision to train the recognition of different inventory, without human intervention. This allows the warehouse outbound process to be sped up, and data exchange to be more seamless.

 

The Cluster offers holistic solutions for Supply Chain Management by

  • partnering with the School of Applied Science to look into increasing the yield and quality of the Food Supply Chain
  • partnering with the School of Sports, Health and Leisure to explore opportunities to improve the efficiency of the Healthcare Supply Chain
  • collaborating with the School of Infocomm in developing Supply Chain 4.0 solutions
  • working with automation and systems engineers for technology adoption