Test and evaluation, certification and systems assurance

Overview

Factory of the Future – comprising the Digital Innovation Lab and the Industrial Digital Transformation Hub – services a range of sectors in training, testing and evaluation, and research and development, including advanced manufacturing, defence, chemical, transport and textiles.

The Factory of the Future and the Digital Innovation Lab are established leaders in Industry 4.0 and 5.0 with multi-disciplinary capabilities and world-class facilities that offer live manufacturing systems testbeds for rapid development, testing and evaluation.

The team includes manufacturing consultants and experts in software engineering (rapid application development) and engineering – offering opportunities for co-creation, experimentation and innovation to prototype, test and evaluate new manufacturing and digital solutions.

Overview

The ARC Training Centre on Surface Engineering for Advanced Materials (SEAM) helps solve critical surface engineering problems faced by industry, while training talented industry-ready graduates for the future.

SEAM has developed coating technology and materials for use in defence, including hydrophilic and hydrophobic surfaces, multi-layer thermal barriers systems, high-temperature resistant coatings, and functional coatings for carbon fibre composites.

Overview

The materials, coatings and manufacturing programs within the institute conduct materials and structural certification work for space and aerospace. The cornerstone of these programs is the ability to give functional characteristics to a surface by applying a coating.

Researchers from the institute work with industry partners to engineer surface coatings – from materials that can protect satellites against wear and tear, to high-temperature materials for hypersonic flight. The institute also develops advanced composites, smart coatings, the ability to embed sensors, and self-cleaning surfaces.

Overview

Space domain awareness (SDA) involves tracking and predicting satellite and space debris orbits to avoid potential collisions – a process involving human decision-making, which requires analysis of large amounts of data on short timescales.

To reduce uncertainty and improve decision-making, Swinburne, in collaboration with industry partners, developed a concept of operations (CONOPS) for real-time follow-up of complex scenarios via smart tasking of dedicated sensors and a focus on human-AI visual analytic workflows.

Our research also investigates decision-making in time-critical situations in human-AI teams, which can be affected by mental workload, stress and situational awareness.

This is achieved by measuring, analysing and assessing cognitive factors, physical factors and skill level through elements including biometrics, eye-tracking and interaction analytics.

Defence applications include providing operational support, as well as command and control.

Overview

Swinburne's Centre for Transformative Media Technologies explores training, planning, analysis, simulation and exploration with virtual reality (VR) and augmented reality (AR).

Applications for VR and AR development include:

• motion capture
• volumetric capture to record 3D human performances
• scanning to map 3D spaces
• creation of 3D environments, as well as VR and AR experiences.

These applications can assist Australia’s defence strategy with cost-efficient training in skills such as equipment maintenance and vehicle operation, simulated environmental training and field medical training, and language and cultural training.

Overview

Swinburne's Manufacturing Futures Research Platform specialises in advanced manufacturing technologies. Key projects in the platform include:

• maintenance, repair, overhaul and upgrade (MRO-U) of defence-grade components (which incorporates microstructural and mechanical testing and repair process validation)
• non-destructive evaluation (ultrasonics)
• additive and subtractive manufacturing of metallic components for naval, aerospace and army applications (including the testing of ferrous and non-ferrous parts and physical property evaluation)

Overview

Swinburne's Intelligent Data Analytics Lab focuses on the research and development of machine learning and intelligent optimisation techniques for tackling real-world data challenges with the aim of facilitating the data-to-discovery and decision process. Applications include:

• deep-learning-based predictive maintenance to extend lifespan and reduce downtime for equipment and systems
• enhancement of naval platform state awareness through data analysis
• remote sensing with artificial intelligence for survelling ground objects and events
• use of satellite data to help manage remote operations
• integration of data-driven and simulation-based approaches for traffic incident management.

Overview

Swinburne’s Mechanical Characterisation Group employs state-of-the-art facilities to evaluate the mechanical performance of various materials and structures subjected to various loadings, including quasi-static and dynamic tension, compression and bending.

The group is able to:

• conduct dynamic mechanical tests on materials at various strain rates (up to 8000 /s) and temperatures (from -50^oC to 500^oC)
• design and fabricate lightweight cellular materials and metamaterials with desired mechanical performance
• employ advanced printers to fabricate continuous fibre-reinforced composite materials and structures
• run computer simulations of structural behaviour

The group also carries out impact tests of structures such as ballistic tests and high speed digital image correlation to capture and precisely measure deformation.

Overview

Swinburne has specialist capabilities in the use of integrated circuit (IC) microchips in complementary metal-oxide semiconductor (CMOS) technology.

The research includes radiation testing of electronics using particle accelerator machines and the use of radiation-hardened electronics against radio frequency attacks for the Department of Defence.

The research also includes silicon photonics (SiPh) chips, which are smaller, more portable and cost-effective, for sensor communications.

Overview

Swinburne undertakes research in crashworthiness, advanced structures and materials, and mechanical properties of novel materials.

We are currently investigating why next-generation road safety roller barriers – vertical steel posts supporting yellow ethylene vinyl acetate rollers – are so effective in providing impact protection and reducing fatalities and serious injuries.

Our research explores:

• the design of lightweight structures and materials with tuneable and prescribed properties and additive manufacturing
• the structural crashworthiness (automotive, marine and aerospace structures) and energy absorption of structures and materials
• the high-speed impact behaviour of alloys and structures
• the design and fabrication of fibre-reinforced polymer laminates

All of these have defence applications.

Overview

Our 6G Research and Innovation Lab leads research into higher frequency 6G wireless networks, which will deliver data speeds faster than 5G to accommodate data intensive applications.

Working with state-of-the-art exposure systems, microscopic and spectroscopic facilities, and an electromagnetically shielded test chamber, the lab conducts biological and electromagnetic research projects, including radiation testing of electronic systems incorporating integrated circuits, which can be sensitive to electromagnetic interference.

Overview

Swinburne specialises in multi-modal artificial intelligence (AI), which processes:

• information from multiple sources including images, videos, and text
• computer vision – bringing super-resolution to images for more accurate detection and classification of content
• the use of AI in big data.

Our work has defence applications in:

• scene understanding for drone-based navigation
• remote sensing through satellite image analysis
• quality and safety control and smart forecasting in areas like land use
• quality and safety control
• monitoring standard operating procedures
• defect detection.