AI Facility Manager

15.06.2021 - 14.12.2021
Auftragsforschungsprojekt

Knowing the state of your building’s mechanical assets at all times provides a distinct edge, as this can predict impending device failures and better organization of maintenance efforts. The breakdown of certain systems at an inopportune time might result in considerable losses. However, by concentrating on ecosystem optimization, these failures can be avoided.

Multisensory setup has been used on pumps, gears, compressors etc. to capture important information of different parameters like sound, vibration or temperature [Ref]. This data can be meaningfully used for monitoring and maintenance. Various statistical models can be used to make inferences and predictions. [WE ADD ONE LINE ON “processing of data and decision making by machine learning and AI moving from the cloud down to the edge.”]

Using generative research techniques, we want to explore the possible reasons behind the failure of the system and the barriers encountered in prevention. We aim to develop a solution for better management. Our objective is to maintain the solution's user friendliness in mind. To begin with we need to understand: How might we comprehend the present ecosystem's flaws? Where is the gap?

Personen

Projektleiter_in

Subprojektleiter_in

Projektmitarbeiter_innen

Institut

Auftrag/Kooperation

  • Siemens AG Ö

Forschungsschwerpunkte

  • Computational Science and Engineering
  • Information and Communication Technology

Schlagwörter

DeutschEnglisch
testbuilding management
condition monitoringcondition monitoring

Externe Partner_innen

  • Siemens AG Österreich