Economically efficient green logistics through cyber physical systems. Economically efficient green logistics through cyber physical systems. This project aims to realize green logistics by researching how to run diesel-powered heavy-duty milk trucks economically and efficiently on liquefied natural gas (LNG) and demonstrating to logistics companies that LNG conversion will reduce operating costs and emissions. Transportation systems account for 18% of Australia's carbon emissions, and diesel-po ....Economically efficient green logistics through cyber physical systems. Economically efficient green logistics through cyber physical systems. This project aims to realize green logistics by researching how to run diesel-powered heavy-duty milk trucks economically and efficiently on liquefied natural gas (LNG) and demonstrating to logistics companies that LNG conversion will reduce operating costs and emissions. Transportation systems account for 18% of Australia's carbon emissions, and diesel-powered logistics vehicles are a major contributor. However, converting these trucks to LNG requires strong evidence to convince logistics companies of the benefits of shifting to green logistics. An increase in logistics productivity is expected to increase Australia’s gross domestic product by $2 billion, while this research should also provide vital data on sustainability issues and LNG conversions.Read moreRead less
Partially Observable MDPs, Monte Carlo Methods, and Sustainable Fisheries. Partially Observable Markov Decision Processes (POMDPs) provide a general mathematical framework for sequential decision making under uncertainty. However, solving POMDPs effectively under realistic assumptions remains a challenging problem. This project aims to develop new efficient Monte Carlo algorithms to significantly advance the application of POMDPs to real-world decision problems involving complex action spaces an ....Partially Observable MDPs, Monte Carlo Methods, and Sustainable Fisheries. Partially Observable Markov Decision Processes (POMDPs) provide a general mathematical framework for sequential decision making under uncertainty. However, solving POMDPs effectively under realistic assumptions remains a challenging problem. This project aims to develop new efficient Monte Carlo algorithms to significantly advance the application of POMDPs to real-world decision problems involving complex action spaces and system dynamics. Both theoretical and algorithmic approaches will be applied to sustainable fishery management --- an important problem for Australia and an ideal context for POMDPs. The project will advance research in artificial intelligence, dynamical systems, and fishery operations, and benefit the national economy.Read moreRead less
Industrial Transformation Training Centres - Grant ID: IC140100032
Funder
Australian Research Council
Funding Amount
$2,119,872.00
Summary
ARC Training Centre for Food and Beverage Supply Chain Optimisation. ARC Training Centre for Food and Beverage Supply Chain Optimisation. With 15 per cent of the Australian workforce involved in food production and annual food exports of $30.5 billion, the food industry is clearly vital to the Australian economy. The National Food Plan White Paper states as a goal for 2025: "The value of Australia's agriculture and food-related exports will have increased by 45 per cent (in real terms), contribu ....ARC Training Centre for Food and Beverage Supply Chain Optimisation. ARC Training Centre for Food and Beverage Supply Chain Optimisation. With 15 per cent of the Australian workforce involved in food production and annual food exports of $30.5 billion, the food industry is clearly vital to the Australian economy. The National Food Plan White Paper states as a goal for 2025: "The value of Australia's agriculture and food-related exports will have increased by 45 per cent (in real terms), contributing to an increase in our gross domestic product." To make these aspirations a reality, safe, sustainable, and cost-effective, food supply chains will be essential. The Training Centre will train the next generation of multi-disciplinary researchers capable of designing and managing these supply chains.Read moreRead less
Industrial Transformation Training Centres - Grant ID: IC190100026
Funder
Australian Research Council
Funding Amount
$4,969,663.00
Summary
ARC Training Centre for Cell and Tissue Engineering Technologies. The ARC Training Centre for Cell and Tissue Engineering Technologies aims to provide training to create a highly skilled workforce for the tissue engineering and regenerative medicine sector and to enhance research performance and innovation in Australia through fundamental and applied research carried out in industry-led PhD projects. The research aims to address major aspects of the manufacturing and commercialisation pathway an ....ARC Training Centre for Cell and Tissue Engineering Technologies. The ARC Training Centre for Cell and Tissue Engineering Technologies aims to provide training to create a highly skilled workforce for the tissue engineering and regenerative medicine sector and to enhance research performance and innovation in Australia through fundamental and applied research carried out in industry-led PhD projects. The research aims to address major aspects of the manufacturing and commercialisation pathway and barriers faced by the sector, namely improving process efficiencies, enabling early-stage scale-up (cell/tissue) and development of the sector's supply chain. The knowledge created and research undertaken would help to accelerate commercialisation in regenerative medicine, tissue engineering and cell therapies.Read moreRead less
Mathematics and computing for integrated stockyard-centric management of mining supply chains. Blended mineral products, such as coal and iron ore, make a strong contribution to Australia's economy. Blending occurs in stockpiles, so to realise product value, stockyard and supply chain operational plans must align with blend targets. This project will provide new mathematical and computational planning tools to maximise this value.