Degree Type

Dissertation

Date of Award

2016

Degree Name

Doctor of Philosophy

Department

Civil, Construction, and Environmental Engineering

Major

Civil Engineering

First Advisor

Yelda Turkan

Abstract

Facility managers face many challenges during their day-to-day practices. Such challenges include identifying spaces within a facility with heating and cooling problems caused by systems faults and malfunctions. In addition, they lack the tools and methods to detect spaces within a facility that have deteriorated equipment and systems malfunction. On the other hand, Facility Management (FM) information systems are complex and provide high quality data. However, they lack interoperability and visualization capabilities and fail to support FM needs. This dissertation aims to detect spaces with faults and failures in buildings. It uses Building Information Modeling (BIM) and other FM information systems to determine intended energy performance and compare with actual energy consumption and other information stored in different FM systems. In addition, the dissertation aims to improve the quality of data collected, which is necessary for corrective and predictive maintenance actions through utilizing visualization and interoperability capabilities of BIM. To achieve that, a framework with different processes and approaches was developed. This framework links data between Industry Foundation Class (IFC) BIM, energy simulation results, Building Energy Management Systems (BEMS), and Computerized Maintenance Management Systems (CMMS) to detect spaces with faults and problematic behavior within a facility. The framework also implements IFC-BIM to link and present alarms reported by FM systems such as BEMS and CMMS. The framework was validated on a case study. The results show that the facility energy performance reflects the faults in its energy management systems. Furthermore, it helps detecting spaces with faults and maintenance needs. Moreover, the proposed framework showed efficiency increase in high-quality maintenance data collection. The framework contributes to the body of knowledge by providing facility managers with a framework that outlines how to use energy simulation and data aggregated from other FM systems and BIM to locate and detect spaces with problematic behavior. In addition, it provides a schema that integrates corrective maintenance data in a 3D IFC-BIM environment. It also helps minimize the lead-time needed by facility managers to collect relevant high quality data and link it to problematic spaces and failed equipment.

Copyright Owner

Firas Adnan Al Shalabi

Language

en

File Format

application/pdf

File Size

140 pages

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