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AI Factory for Mobile Machinery in Mines

Reference number
Coordinator Luleå tekniska universitet
Funding from Vinnova SEK 5 000 000
Project duration September 2022 - September 2025
Status Ongoing
Venture Advanced digitalization - Enabling technologies
Call Advanced and innovative digitalization 2022

Purpose and goal

The objective of ‘AI Factory for Mobile Machinery in Mines (AIF/M)’ is to enable a Digital Twin through development and provision of an integrated platform and toolkit for fact-based decision-making in mining asset management of mobile machines, empowered by AI and digital technologies. AIF/M will have a special focus on aspects of: a) data and models sharing ; b) information-driven analytics aimed for asset management; c) cybersecurity; d) new innovative business models; e) AI-solution based on distributed computing.

Expected results and effects

AIF/M will deliver the following artefacts: * A need-map for asset management of mining machines * A technology platform for decision support in the production phase This platform is based on AI and digital technology to support asset management * A demonstrator based on Digital Twin This integrated demonstrator is used for verification of developed and integrated components based * A roadmap for digitalisation and AI in the production phase This can be used by the project´s internal stakeholders and external stakeholders for the implementation

Planned approach and implementation

AIF/M’s will be executed in four phases: * Phase I, identify, map, and describe mining asset management with a focus on fleet management needs of data and information for fact-based decision-making * Phase II, develop and establish a common distributed cloud/fog/edge-based platform for the development, verification, integration, and demonstration of developed AI algorithms * Phase III, integrate identified internal and external data sources into the project´s cloud/fog/edge environment * Phase IV, develop & implement AI algorithms in the project´s cloud/fog/edge environment

External links

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 31 October 2022

Reference number 2022-01707

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