Advanced planning systems for vertically integrated supply chain management. This project will integrate various algorithms into an adaptive, dynamic and intelligent system that deals with the vertically integrated supply chains. The outcomes include publications in the quality outlets, generation of intellectual property, and dissemination of this research amongst the research and business communities.
Industrial Transformation Training Centres - Grant ID: IC190100017
Funder
Australian Research Council
Funding Amount
$3,703,664.00
Summary
ARC Training Centre for Integrated Operations for Complex Resources. This Training Centre aims to increase value in mining through clever applications of ‘lean processing’ and train the next generation of scientists and engineers in advanced sensors and data analytics in complex resources; knowledge priorities for the mining industry. Sensor information will be linked to the resource’s in-place knowledge to enable data analytics of all embedded knowledge. Processing can then be tuned to resource ....ARC Training Centre for Integrated Operations for Complex Resources. This Training Centre aims to increase value in mining through clever applications of ‘lean processing’ and train the next generation of scientists and engineers in advanced sensors and data analytics in complex resources; knowledge priorities for the mining industry. Sensor information will be linked to the resource’s in-place knowledge to enable data analytics of all embedded knowledge. Processing can then be tuned to resource attributes, maximising value ‘on the fly’. Benefits will include increasing certainty on product quality and maximising throughput and recovery. Outcomes will include new tools to rapidly model geological and geometallurgical uncertainty with sensor inputs, to track the resource to product and enhance interpretation.Read moreRead less
Data-driven water quality treatment management decision support system. Data-driven water quality treatment management decision support system. This project aims to develop a robust decision support system to predict manganese and the character and concentration of dissolved organic matter in drinking water reservoirs, using intelligent algorithms and data collected through remote autonomous instrumentation. These predicted water quality parameters could be used as model input variables to provi ....Data-driven water quality treatment management decision support system. Data-driven water quality treatment management decision support system. This project aims to develop a robust decision support system to predict manganese and the character and concentration of dissolved organic matter in drinking water reservoirs, using intelligent algorithms and data collected through remote autonomous instrumentation. These predicted water quality parameters could be used as model input variables to provide real-time decisions for plant operators on the required treatment regime for incoming raw water, and advise them on the optimal reservoir offtake depth. This will potentially minimise treatment costs and health risks for consumers. The ultimate goal is to significantly enhance current water supply management practices.Read moreRead less
Developing group-based elicitation methods to improve decision making. This project aims to develop an elicitation methodology enabling multiple members of a team to contribute to the same technical problem - enabling expertise to be accurately combined while avoiding group and individual sources of bias. Good elicitation methods minimise bias in estimates and forecasts - which otherwise erode value and lead to sub-optimal decision making. Existing methods, however, ignore group structures; that ....Developing group-based elicitation methods to improve decision making. This project aims to develop an elicitation methodology enabling multiple members of a team to contribute to the same technical problem - enabling expertise to be accurately combined while avoiding group and individual sources of bias. Good elicitation methods minimise bias in estimates and forecasts - which otherwise erode value and lead to sub-optimal decision making. Existing methods, however, ignore group structures; that is that decisions made by, or on, the advice of teams have different characteristics than individual decisions and often preclude the use of methods designed to limit individuals' biases. By encoding the method into a computerised tool the project will assist public and private sector enterprises to improve group decision making.Read moreRead less
Immersive Technologies for Rapid Metallic Tank Inspection and Repairs. Metal tank silos house some of the most dangerous chemicals, which erode the internal structure of the tank over time. It is critical to check the integrity of the tank to prevent disasters from occurring. NDE solutions uses a rapid motion scanner (RMS) to scan the interior surface of the container while it is still full of its storage material. It is the aim of this project to use Augmented Reality, to overlay the scan provi ....Immersive Technologies for Rapid Metallic Tank Inspection and Repairs. Metal tank silos house some of the most dangerous chemicals, which erode the internal structure of the tank over time. It is critical to check the integrity of the tank to prevent disasters from occurring. NDE solutions uses a rapid motion scanner (RMS) to scan the interior surface of the container while it is still full of its storage material. It is the aim of this project to use Augmented Reality, to overlay the scan provided by the RMS, onto the worker's view of the tank, control the robot via. hand gestures, and facilitate remote training/guidance. The result will allow for inspection workers to quickly and accurately the location of critical failures, without performing the hazardous procedures of internal tank inspection. Read moreRead less
Impact of natural organic matter and nutrients on water quality: identification of catchment sources and attenuation processes. Development of a decision support model for land-use selection that protects water resources will be of significant benefit to the water industry. The outcomes of this project will provide water and catchment managers with a technology that significantly secures the supply of resources for high quality drinking water.