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AI Factory for Prognostics and Health Management

Reference number
Coordinator Luleå tekniska universitet
Funding from Vinnova SEK 5 000 000
Project duration February 2023 - February 2026
Status Ongoing
Venture Strategic innovation programme for process industrial IT and automation – PiiA

Purpose and goal

The objective of ‘AI Factory for Prognostics and Health Management (AIF/P)’ is to enable a Digital Twin for PHM and asset management through the 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/P will deliver capabilities described according to the industrial ´Use Cases´ (UC), i.e. UC01 and UC02.

Expected results and effects

AI Factory for Prognostics and Health Management (AIF/P)’s mission is to enable an effective and efficient asset management regime through the development and provision of mechanisms that provide insight into assets’ current health and also to assets’ estimated health. One of the approaches to enable this health monitoring and estimation is through so-called Prognostics and Health Management (PHM) that also contributes to enablement of predictive maintenance and Digital Twin.

Planned approach and implementation

AIF/P will develop:: a)in Phase I, in detail identify, map, and describe mining AM with a focus on prognostics & health management needs of data and information for fact-based decision-making b)in Phase II, develop and establish a common distributed cloud/fog/edge-based platform for the development of AI algorithms c)in Phase III, integrate relevant and identified internal and external data sources , which arenecessary to develop the AI-based solution d)in Phase IV, develop & implement AI algorithms in the cloud/fog/edge environment, for data analysis and decision support

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 5 March 2023

Reference number 2022-03584

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