Trustworthy Predictive Maintenance TPdM
Research Project, 2022
– 2025
Purpose and goal
Predictive maintenance (PdM) has the highest potential to generate business value in the era of industrial digitalization. PdM solutions must be extended to provide interpretable results with increased accuracy in predictions through trustable decision support systems to achieve the vision of failure-free production. Therefore, the TPdM project aims to design human-centered decision support prototypes for PdM to achieve actionable decisions using advanced data science and scale up the innovative PdM applications in the Swedish manufacturing industry.
Expected results and effects
The expected results are identified models for roadmaps, models and methods for trustworthiness in PdM, designed and deployed software prototype for TPdM, and dissemination materials for spreading gained knowledge (e.g., lifelong learning). The impact of these results is efficient maintenance planning with reduced downtime, cost efficiency, increased OEE, productivity, robustness, resource efficiency, collaboration, and competence in smart maintenance as well as advanced data analysis for the competitiveness of the Swedish industry.
Participants
Ebru Turanoglu Bekar (contact)
Chalmers, Industrial and Materials Science, Production Systems
Anders Skoogh
Chalmers, Industrial and Materials Science, Production Systems
Collaborations
AB Volvo
Sweden
Capgemini Sverige AB
Sweden
Husqvarna AB
Huskvarna, Sweden
SKF
Göteborg, Sweden
Siemens AB
Sweden
University of Skövde
Skövde, Sweden
Funding
VINNOVA
Project ID: 2022-01710
Funding Chalmers participation during 2022–2025
Related Areas of Advance and Infrastructure
Sustainable development
Driving Forces
Production
Areas of Advance