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Project Topic
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AI-COSTSQO partners come together to create an eco-efficient and sustainable stone exploitation by using non-invasive survey, optimize production, reducing waste, energy and water usage. Thus, the degree of negative social effects of mining activities, which have increased in recent years, will also be reduced. The interest area of the project will cover both currently operating mines and non-operating deposits. With the project work, an effort will be made to evaluate the current situation, to predict the financial profitability of virgin deposits and the amount of waste to be produced. The project, which has an interdisciplinary character, consists of academic people who are experts in their fields. These people have a lot of projects and academic studies related to the subject, and they are completely locking at the target. The operability of the stone deposit as a rock mass is mostly assessed by the presence of discontinuities. Our project will be primarily the basis on the modelling of the existence of these using Analytical, Mathematical, Statistical, Machine Learning and Big Data solutions. In addition, realistic survey methods will be used as mainly data. The innovative model will be created combining several approaches, like calculating the maximum cuboid volumes that fit into natural polyhedrons and the orientation of the cutting grid, considering discontinuities and planning to cut directions and spatial position of general planning of quarry using block dimension distributions. In this concept, six work packages have been designed and distributed to the partners according to their specialisation. Although there is no exact data for natural stone quarries recovery rates, it is well known these rates may be decreased to about 10% in many quarries. We believe that the project outcomes, combined innovative survey methods and new optimization algorithms, will significantly improve the recovery rates and decrease waste production in stone quarries.
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