Condition-based maintenance optimisation for Australian sugar industry. The aim of this project is to develop innovative methodologies for the implementation of condition-based maintenance in the sugar milling industry. This is designed to optimise the allocation of limited maintenance resources and to significantly reduce the $350 million spent on maintenance in the industry each year. New methodologies will account for the seasonality of production and the complexity of allocating limited main ....Condition-based maintenance optimisation for Australian sugar industry. The aim of this project is to develop innovative methodologies for the implementation of condition-based maintenance in the sugar milling industry. This is designed to optimise the allocation of limited maintenance resources and to significantly reduce the $350 million spent on maintenance in the industry each year. New methodologies will account for the seasonality of production and the complexity of allocating limited maintenance resources across numerous equipment items and different production sites. The intended outcome of the project will improve the efficiency of maintenance and hence the global competitiveness of the Australian sugar industry.Read moreRead less
ARC Centre of Excellence for Mathematical and Statistical Frontiers of Big Data, Big Models, New Insights. In today's world, massive amounts of data in a variety of forms are collected daily from a multitude of sources. Many of the resulting data sets have the potential to make vital contributions to society, business and government, as well as impact on international developments, but are so large or complex that they are difficult to process and analyse using traditional tools. The aim of this ....ARC Centre of Excellence for Mathematical and Statistical Frontiers of Big Data, Big Models, New Insights. In today's world, massive amounts of data in a variety of forms are collected daily from a multitude of sources. Many of the resulting data sets have the potential to make vital contributions to society, business and government, as well as impact on international developments, but are so large or complex that they are difficult to process and analyse using traditional tools. The aim of this Centre is to create innovative mathematical and statistical models that can uncover the knowledge concealed within the size and complexity of these big data sets, with a focus on using the models to deliver insight into problems vital to the Centre's Collaborative Domains: Healthy People, Sustainable Environments and Prosperous Societies.Read moreRead less
Pathways to agri-food supply chains that co-benefit people and nature. This project aims to improve biodiversity outcomes of agricultural food production and consumption, and expects to generate new knowledge about impacts of interventions and shocks on the environment, human health and livelihoods in agri-food systems. This will be achieved using an interdisciplinary approach that accounts for uncertainties in links between farmers, suppliers, consumers and supply-chain outcomes. The expected o ....Pathways to agri-food supply chains that co-benefit people and nature. This project aims to improve biodiversity outcomes of agricultural food production and consumption, and expects to generate new knowledge about impacts of interventions and shocks on the environment, human health and livelihoods in agri-food systems. This will be achieved using an interdisciplinary approach that accounts for uncertainties in links between farmers, suppliers, consumers and supply-chain outcomes. The expected outcome is a value of information framework for identifying nature-friendly policies and actions with co-benefits for human well-being. Benefits include sustainability pathways with win-win outcomes for people and nature, and improved ways of meeting international commitments such as Sustainable Development Goals.Read moreRead less
Maintenance Optimisation in Rail Infrastructure Systems for Coal and
Iron Ore Exports. Coal and iron ore exports, worth around 55 per cent of Australia's export earnings, critically depend on the transport capacity provided by Australia's rail infrastructure. Maintenance plays a crucial role in ensuring that infrastructure components are in a condition to provide safe, reliable, and efficient transport. However maintenance activities also reduce the system capacity, and are costly. It is thus c ....Maintenance Optimisation in Rail Infrastructure Systems for Coal and
Iron Ore Exports. Coal and iron ore exports, worth around 55 per cent of Australia's export earnings, critically depend on the transport capacity provided by Australia's rail infrastructure. Maintenance plays a crucial role in ensuring that infrastructure components are in a condition to provide safe, reliable, and efficient transport. However maintenance activities also reduce the system capacity, and are costly. It is thus critical to sustaining the growth and competitiveness of Australia's coal and iron ore exports that maintenance is optimised so as to maximise system efficiency and delivered capacity. The project aims to achieve this by the development of new decision support technologies embedding innovative decision-making models and algorithms.Read moreRead less
Large Markov decision processes and combinatorial optimisation. Markov decision processes continue to gain in popularity for modelling a wide range of applications ranging from analysis of supply chains and queueing networks to cognitive science and control of autonomous vehicles. Nonetheless, they tend to become numerically intractable as the size of the model grows fast. Recent works use machine learning techniques to overcome this crucial issue, but with no convergence guarantee. This project ....Large Markov decision processes and combinatorial optimisation. Markov decision processes continue to gain in popularity for modelling a wide range of applications ranging from analysis of supply chains and queueing networks to cognitive science and control of autonomous vehicles. Nonetheless, they tend to become numerically intractable as the size of the model grows fast. Recent works use machine learning techniques to overcome this crucial issue, but with no convergence guarantee. This project aims to provide theoretically sound frameworks for solving large Markov decision processes, and exploit them to solve important combinatorial optimisation problems. This timely project can promote Australia's position in the development of such novel frameworks for many scientific and industrial applications.Read moreRead less