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Talk | Hållbar produktion

Ever since the dawn of humanity prediction and forecasting the future have been in focus. One of the main objective with the ongoing transition towards smart factories is increased predictability of system capability and performance. In this context machines and tools will have inbuild capabilities to make self-diagnose, become self- learning and possess the ability to perform self-adjustments. In this seminar, we will show new technologies for industrial analytics and data-driven solutions for increased manufacturing performance and maintenance. We will also discuss the combination of  data-driven with  knowledge-based for a hybrid physics-based analytics approach that relieves the weaknesses of both individual approaches by leveraging their complementary strengths.

The seminar summarizes a number of ongoing and completed research activities in the field of industrial analytics and maintenance among other projects with Swedish industry and the European Space Agency (ESA). The talk will be given in English.

 

 

 

 

 


Medverkande

Andreas Archenti 

Professor , KTH

Dr. Károly Szipka

Postdoctor , KTH

Dr. Maheshwaran Gopalakrishnan

Researcher , KTH

Eleonora Iunusovai

Phd student , KTH

Péter Troll

Research engineer , KTH