A complete Stochastic Trans-shipment Decision Model (STDM) to assist logistics practitioners to make cost optimised decisions. This project aims to implement a decision-makng model based on a new mathematical theory in dealing with supply and demand problems for businesses. The purpose is to minimise the expected logistics costs for goods trans-shipment operations along the supply chain, thereby maximising profits and enhancing the competitiveness of Australian companies.
Learned Academies Special Projects - Grant ID: LA170100023
Funder
Australian Research Council
Funding Amount
$345,000.00
Summary
Decadal plan for technology research in Australia. This project aims to assess the research needs of key Australian industry sectors, based on likely scenarios for Australia in 2030 and industry’s readiness to adopt new technology. The project expects to highlight opportunities for research organisations and companies to deliver research outcomes and to identify skilled people to support Australian competitiveness. These opportunities can then be mapped against current research efforts to help p ....Decadal plan for technology research in Australia. This project aims to assess the research needs of key Australian industry sectors, based on likely scenarios for Australia in 2030 and industry’s readiness to adopt new technology. The project expects to highlight opportunities for research organisations and companies to deliver research outcomes and to identify skilled people to support Australian competitiveness. These opportunities can then be mapped against current research efforts to help provide a road map for future research strategies. The project outputs will help guide the implementation of programs by industry and research organisations, and ensure a higher quality workforce with skills matched to future demand.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE210100368
Funder
Australian Research Council
Funding Amount
$396,071.00
Summary
Algorithmic management and the future of work: lessons from the gig economy. The gig economy is at the forefront of ‘algorithmic management’, a major technological disruption of management, work, and employment. Used to replace humans as organisational managers, these systems are projected to spread wide across the Australian economy yet remain poorly understood. This study will systematically interrogate the nature and operations of algorithmic management across platforms operational in the Aus ....Algorithmic management and the future of work: lessons from the gig economy. The gig economy is at the forefront of ‘algorithmic management’, a major technological disruption of management, work, and employment. Used to replace humans as organisational managers, these systems are projected to spread wide across the Australian economy yet remain poorly understood. This study will systematically interrogate the nature and operations of algorithmic management across platforms operational in the Australian gig economy. It will explore the design and oversight of, workers’ experiences with, and the role end-users play in sustaining these systems. The study will generate state-of-the-art academic knowledge and provide guidance to policy makers on how to respond to, and where necessary regulate, algorithmic management.Read moreRead less
Modelling network innovation performance capability: a multidisciplinary approach. Innovation is created in complex network interactions.
By combining agent-based and fuzzy logic modelling, this project will identify combinations of resources to generate new ideas/technologies. This will enable managers and policy makers to understand the mechanisms behind innovation and implement policies aimed at enhancing innovation processes.
Responsible Urban Innovation with Local Government Artificial Intelligence. Artificial intelligence (AI) is not only becoming an integral part of urban services, but also impacting and shaping the future of cities and societies. However, the current AI practice has shown that urban innovation without responsibility generates more problems than it solves. Especially, the absence of a deep understanding of the costs, benefits, risks and impacts of deploying government AI systems creates negative e ....Responsible Urban Innovation with Local Government Artificial Intelligence. Artificial intelligence (AI) is not only becoming an integral part of urban services, but also impacting and shaping the future of cities and societies. However, the current AI practice has shown that urban innovation without responsibility generates more problems than it solves. Especially, the absence of a deep understanding of the costs, benefits, risks and impacts of deploying government AI systems creates negative externalities and serious concerns in the society. This project will generate new knowledge on the most appropriate approaches for local governments to engage with AI to achieve responsible urban innovation. The project outcomes will include responsible AI adoption and implementation pathways for Australian local governments.Read moreRead less
Industrial Transformation Training Centres - Grant ID: IC200100022
Funder
Australian Research Council
Funding Amount
$4,883,406.00
Summary
ARC Training Centre for Information Resilience. The proposed centre aims at building workforce capacity in Australian organisations to create, protect and sustain agile data pipelines, capable of detecting and responding to failures and risks across the information value chain in which the data is sourced, shared, transformed, analysed and consumed. Building on strong foundations of responsible data science, the centre will bring together end-users, technology providers, and cutting-edge researc ....ARC Training Centre for Information Resilience. The proposed centre aims at building workforce capacity in Australian organisations to create, protect and sustain agile data pipelines, capable of detecting and responding to failures and risks across the information value chain in which the data is sourced, shared, transformed, analysed and consumed. Building on strong foundations of responsible data science, the centre will bring together end-users, technology providers, and cutting-edge research, to lift the socio-technical barriers to data driven transformation and develop resilient data pipelines capable of delivering game-changing productivity gains that position Australian organisations at the forefront of technology leadership and value creation from data assets. Read moreRead less
A highly sensitive and selective nano-engineered sensor for the online monitoring of mercury vapour emissions from harsh industrial processes. The Australian alumina and aluminium industries contribute over $11 billion export income annually. All refineries, except one, operate in rural areas and are the main economic drivers in these regions. In order to maintain the industry's commitment to reduce the environmental impact of its processes and remain economically sustainable, innovative technol ....A highly sensitive and selective nano-engineered sensor for the online monitoring of mercury vapour emissions from harsh industrial processes. The Australian alumina and aluminium industries contribute over $11 billion export income annually. All refineries, except one, operate in rural areas and are the main economic drivers in these regions. In order to maintain the industry's commitment to reduce the environmental impact of its processes and remain economically sustainable, innovative technologies are required to monitor mercury emissions. The aim of this project is to develop robust sensors, for online monitoring of mercury vapours, that operate under challenging industrial environments. This project will also provide excellent training for young researchers in established international industrial research groups, thereby meeting skill shortages in the Australian resource sector.Read moreRead less
AI Assisted Probabilistic Structural Health Monitoring with Uncertain Data. This project aims to develop an advanced Artificial Intelligence (AI) assisted probabilistic structural health monitoring approach for civil engineering structures. The developed approach applies novel deep learning techniques with a large amount of data measured from uncertain and complex environment, for reliable structural condition monitoring and performance prediction. This project expects to make a step change in d ....AI Assisted Probabilistic Structural Health Monitoring with Uncertain Data. This project aims to develop an advanced Artificial Intelligence (AI) assisted probabilistic structural health monitoring approach for civil engineering structures. The developed approach applies novel deep learning techniques with a large amount of data measured from uncertain and complex environment, for reliable structural condition monitoring and performance prediction. This project expects to make a step change in data mining and interpretation. Expected outcomes of the project include novel AI assisted approaches to conduct probabilistic structural condition monitoring with sensitive features and future structural performance prediction. This will provide significant benefits to infrastructure asset owners to reduce maintenance costs.Read moreRead less
Maximising Bioenergy Recovery from Sewage Sludge. Sewage treatment is producing large amounts of sewage sludge, which represents a substantial, but largely untapped, energy source. This project aims to develop and demonstrate an innovative, economically attractive and environmentally friendly technology, and the underpinning science, to maximize bioenergy recovery from sewage sludge. The technology is based on the treatment of sludge using free ammonia, a by-product of sewage treatment. This pro ....Maximising Bioenergy Recovery from Sewage Sludge. Sewage treatment is producing large amounts of sewage sludge, which represents a substantial, but largely untapped, energy source. This project aims to develop and demonstrate an innovative, economically attractive and environmentally friendly technology, and the underpinning science, to maximize bioenergy recovery from sewage sludge. The technology is based on the treatment of sludge using free ammonia, a by-product of sewage treatment. This project is expected to benefit Australia by substantially reducing the reliance on fossil fuels and accelerating a shift to affordable renewable energy. The outcomes of the project would provide significant energy, economic, environmental and social benefits for Australians. Read moreRead less
Bio-electrochemical sulfate reduction and sulfur recovery without external carbon source. Highly acidic waterways and mining wastewaters create major environmental challenges in inland Australia. This project will use novel, solar driven biological processes to remove the acid and metals from these streams and enable beneficial reuse of the water and other resources recovered in the process.