Machine Learning drives Automated Fault Detection and Diagnostics and predictive maintenance.
Digital twins based on Machine Learning (ML) will make the air conditioning, refrigeration and heat pump systems more reliable and efficient. This presentation shares experiences of using ML for Automated Fault Detection and Diagnosis (AFDD) that reduce total cost of ownership and down-time.
Themen
Wann & Wo
Einzelheiten
Format:
Vortrag
Language:
Englisch
Session Beschreibung
Background
Digital twins based on Machine Learning (ML) will change maintenance practices in the air conditioning, refrigeration and Heat Pump industry. Our industry uses 20 % of the global electricity and pressure to reduce the carbon footprint and total cost of ownership is increasing. Experience shows that an average saving potential of 25 % is realistic without replacing equipment.
Digital Twins are powerful tools for AFDD
The presentation highlights the potential and experience of using ML to increase accuracy and reduce engineering time for Automated Fault Detection and Diagnosis (AFDD). ML will also be used in BMS systems to reduce loads and optimise controls, but focus is on AFDD.
ML will drive the paradigm sh ...
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