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
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