Research

We solve complex capability development challenges through expert analysis, creative thinking, and interdisciplinary methods.

Personalise
Hand typing on a laptop keyboard with digital analytics dashboard on the screen

Projects

  • Objectives & scope

    The Joint Casualty Evacuation Model (JCEM) is a simulation tool that maps the flow of casualties, treatment, and evacuation under battlefield conditions. It helps Defence identify bottlenecks, test scenarios, and improve planning for medical evacuation. 

    Partners / funding bodies

    DSTG 

    Achievements / milestones

    • Developed the Joint Casualty Evacuation Model (JCEM) to simulate triage, treatment, and evacuation flows. 
    • Validated model logic and ran baseline scenarios demonstrating bottlenecks, delays, and resource constraints. 
    • Produced measurable insights on survival, timelines, and asset utilisation to support Defence planning. 
  • Objectives & scope

    To deliver simulation-based evidence quantifying the costs and benefits of replacing the ADF’s current palletised supply chain with a modular system (e.g., JMIC). The configurable event-driven simulation models current and future ADF supply chains, using VIPA scenarios, to assess demand satisfaction, cost, time, utilisation, and resilience. 

    Partners / funding bodies

    Australian Defence Force – Land Mobility & Support Program 

    Achievements / milestones

    • Developed configurable event-driven simulation integrating VIPA data
    • Modelled both current pallet-based and proposed modular systems
    • Generated performance metrics including demand satisfaction, cost of ownership, and system resilience
  • Objectives & scope

    This project supports the Australian Army in strengthening capability planning and decision-making. It focuses on: 

    • Enhancing Army deployability and readiness.
    • Reducing lifecycle costs across acquisition, updates, and retirement of assets.
    • Developing an integrated framework to support long-term planning and resource optimisation.

    Partners / funding bodies

    Delivered within the Army Capability domain

    Achievements / milestones

    • Developed advanced simulation and optimisation models tailored to Army capability needs. 
    • Applied recognised analytical methods to assess system performance and inform strategic planning. 
    • Demonstrated how operational analysis approaches can be extended to support more holistic, mission-focused frameworks. 
  • Objectives & scope

    UNSW Canberra partners with the University of Cambridge's Digital Manufacturing on a Shoestring programme to help small and medium manufacturing enterprises across ACT and NSW embrace affordable digital solutions that typically cost under $1,500. The programme addresses real production challenges through simple, low-cost technologies – starting with problems that matter most to manufacturers, such as job location tracking, supply chain monitoring, and power management. Working closely with NSW Department of Primary Industries and Regional Development, we deliver hands-on workshops and deploy practical starter solutions that help regional manufacturers become more productive, resilient, and sustainable – one digital step at a time. 

    Partners / funding bodies

    • University of Cambridge
    • University of Technology Sydney
    • NSW Small Business Month

    Achievements / milestones

    • Over 20 companies engaged across ACT and regional NSW
    • Successful deployment of low-cost digital solutions for reducing electricity costs
    • Strong government partnerships facilitating broader industry reach
    • Proven model for scaling affordable digitalisation across regional manufacturing

Current research

Digital Engineering’s role in reaching Net Zero: Six critical factors that will make or break success

Digital Engineering (DE) is a key enabler in the transition to net zero. It offers integrated tools and methods that help organisations manage emissions across direct operations, purchased energy, and entire value chains. Unlike traditional approaches that often require trade-offs between sustainability and performance, DE supports optimisation across competing objectives. It uses technologies like digital twins, model-based systems engineering, and digital threads.

Explore