TRUSTCM - TRUSTed decision-making system for Cognitive Manufacturing
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TRUSTCM aims at developing a new decision-making system based on machine learning (ML) and data analytics that can be trusted by providing meaningful explanations of the decisions made. This can be achieved either by improving the structure of the ML model or augmenting the training data with semantic explanations. TRUSTCM will enable efficient support for the manufacturers and contribute to overcoming the challenges of integrating intelligent solutions into the Industry 4.0 framework. As a case study, the outcome of TRUSTCM will be applied to the Volvo Electric Site viewed as a manufacturing process and simulated in the Volvo Simulators at MDH.
| First Name | Last Name | Title |
|---|---|---|
| Daniel | Sundmark | Professor |
| Anas | Fattouh | Associate Professor |
| Markus | Bohlin | Docent,Professor |
A Real-Time Optimization Model for Production Planning in Quarry Sites (Apr 2021) Anas Fattouh, Markus Bohlin, Daniel Sundmark International Conference on Industrial Engineering and Applications (ICIEA 2021)
