The proposed project aims to improve the prediction of mineral resources for better decision making throughout a mining project, that is, to decide whether to reject or to process extracted material using machine learning algorithms. This will help maximize profit for mining companies while minimizing environmental impact as the correct material will be processed more […]

This work aims to take the academic research one step further to customize recommendations based on academic research findings on the identification and valuation of non-technical risks. It aims to improve the operationalization of the corporate strategy in the investment decision criteria guideline that involves both risks to the projects and risks to the people.

The Centre for Operations Excellence Industry Projects 2019 consists of seven sub-projects sponsored by five different industry partners. Each sub-project represents an important challenge for its sponsor. These sub-projects include Extracting data from unstructured text of NOTAMs to assess relevance (Boeing 1), Developing a fix effectiveness engine to perform data-driven predictive maintenance (Boeing 2), Initial […]