The Client

BDC were engaged by an Engineering firm that monitors the operational performance of a large Enterprise Data Centres.

They wanted to investigate possible efficiency improvements particularly energy cost savings.

The Challenge

The large Data Centre operator had engaged an Engineering firm to help optimise their energy efficiency of one of their key data centres. Energy costs are a significant cost to their business model.

The Solution

Data from a large enterprise data centre were input to the BDC causal analytics algorithms. The objective was to identify some known, but also unknown but suspected cause-effect relationships, between the components of the data centre’s HVAC system (heating, ventilation and air conditioning): temperature, humidity, air flow rates inlet and outlet, differential pressures and equipment status parameters of the computer servers and equipment.

The Results

Our Causal AI Engine results provided new insights on how monitoring data for the cause-effect dynamics can enable the identification and implementation of significant maintenance cost savings.