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.


Ebru Turanoglu Bekar (contact)

Chalmers, Industrial and Materials Science, Production Systems

Anders Skoogh

Chalmers, Industrial and Materials Science, Production Systems


AB Volvo


Capgemini Sverige AB


Husqvarna AB

Huskvarna, Sweden

Siemens AB



Göteborg, Sweden

University of Skövde

Skövde, Sweden



Project ID: 2022-01710
Funding Chalmers participation during 2022–2025

Related Areas of Advance and Infrastructure

Sustainable development

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