At The Forefront of Mining Technologies

AI Data flow processes and circular waste strategies of Chimera Minerals.

Chimera’s AI Digital circular economy discussion combines data flow processes and circular economic strategies for minimizing waste, taking the form of mill tails, waste rock, or overburden. Circular Economy data flow processes start from 1) data acquisition and are followed by 2) data integration and 3) data analysis. Additionally, 4) data sharing is identified as an important phase, when structuring and grouping digital technologies for the circular economy solutions. The linkage between data flow processes and circular strategies identified by includes solutions to cover industrial symbiosis to restore, reduce and avoid material losses.

The implementation of these strategies and how effectively data is presented or generated into knowledge, can vary from descriptive data collection towards predictive and prescriptive data analytics. Digital solutions supporting data flow processes advance the circular economy approach and reduce the environmental and social footprint. However, data acquisition, data management and data analytics demand considerable amounts of energy, and in addition, digital hardware and electronic devices require numerous natural mineral resources. Therefore, the impacts of the implementation of digital technologies are important to first understand, and then implement.

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Digital technologies, many of them already supporting waste management, can be divided into three application levels such as processes, products and platforms and their related technologies such as sensor technologies, machine vision, artificial intelligence, the IoT and Distributed Ledger Technologies (DLT). The waste material data of the mining processes relates to the hierarchical levels of substances and materials, rather than component, product, or product system levels. Data acquisition, data management and data analytics of processes and products are related, for example, to the chemical composition, and physical and chemical properties of substances and materials. The mining waste reduction and reprocessing strategies can be supported by process monitoring and material detection (ore sorting) technologies, such as spectroscopy, machine vision, image analysis or pattern recognition. 

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Our AI Digital Solutions support​, reduce, reprocess and downcycle strategies.Digitalization is considered as an enabler for the circular economy through multiple flow streams, for example, by supporting in the closure of material loops, by monitoring waste and water streams, by providing accurate data and information about the availability, location, quantity, and quality of materials, and by controlling the process more efficiently.

Chimera’s use of its dedicated, geochemical, geospatial, and geochronological artificial intelligence (AI), machine learning, virtual and augmented geo-mining, automation and autonomous design of processing circuits, digital infrastructure and data security are identified as the main contributors to the digital transformation of the raw materials sector and to the optimization of processes, resource efficiency and productivity, also to support waste prevention and data generation for waste valorization.

Furthermore, Chimera’s digital platforms can facilitate the valorization of virgin ore deposits, or mine tailings by new and alternative waste-to-resource evaluations, and market-matching.

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Chimera’s AI, named Hal, was built ground up for mining technology and processes, including geo-mining, material flow location, material quantity and quality, and timing data. HAL is the only AI platform integrating tectonics, glaciation, volcanics, and geochemical/geospatial data to arrive at well-reasoned predictions.

Chimera’s AI Mining Platform will connect consumers and our wholly owned subsidiary producers, allow development of services and dematerialization, industrial symbiosis; as such, Chimera’s Mining Platform will support recovery of secondary raw materials otherwise left untouched. The AI digital planning and management tools for mine closure are proposed instead of the traditional written plans, and they cover aspects related to the management and treatment of mill tailings, waste rock and water quality, and the valorization of strategic metals and materials economically extractable.