An algorithmic module toolkit to support quality management for building performance

Abstract

Data from building automation systems is so far used for the operation of building systems and components only. The following work shows how this data can be used to enhance the building’s performance by strategically detecting potential sources for building optimization. With this method, faults and optimization potentials of the building operation can be detected; thus, the quality gap regarding efficiency and comfort aspects between design and operation can then be reduced. Furthermore, the intelligent use of data enables the realization of economic savings to support facility management with regards to increasingly complex HVAC systems. Effective quality management – rapid, transparent and cost effective – is carried out with the aid of digital methods, which are already state of the art in other industries.