| description abstract | The objective of enterprise building infrastructure management is to provide optimal allocation of maintenance, rehabilitation, and repair (MR&R) resources and to preserve the condition of building components over a planning horizon. While most approaches in the literature have studied it as a finite resource allocation problem, the presence of an underlying building network configuration has not been fully explored. The development of a network model encompassing interrelated building components introduces challenges as well as opportunities for MR&R decision making and optimized building preservation, which cannot adequately be managed using the existing decision-making frameworks. One challenge to enterprise building portfolio management is lack of understanding of the effect of one component’s condition state on another. Building component network-level optimization is not available as in other infrastructure domains, which makes calculating the benefit of component work activities on other building components very difficult to determine. This research focuses on using structured query language (SQL) based association rule mining to find frequent patterns of observed condition deterioration among different component types. This work introduces a new metric, negative effective deterioration, which is based on actual deterioration observed from inspection data relative to expected condition states. Frequent patterns of antecedent and consequent component pairs having negative effective deterioration states are discovered, and support and confidence factors indicate the strength of these network-level connections. The building component network model can improve enterprise work planning by considering the effects of negative effective deterioration on other components. This work uses case studies and data from the US Department of Defense (DoD), which owns and operates over 275,000 buildings totaling nearly 2.2 billion gross square feet (GSF) and $705 billion in plant replacement value. This paper presents a conceptual model to support building system condition assessment and MR&R decision making. This process can decrease the long-term deferred deficiency backlog by focusing limited MR&R resources not only on the components in the worst condition, but on those that would have the most adverse effect on the condition of associated components. | |
