Nowadays, facility managers and related staffs are facing with much maintenance requests every day. The more complicated building system generates the more diverse and complex maintenance issues. With the limited budget and staff, not all the maintenance requests can be solved immediately. To schedule the maintenance work, facility managers first consider the impact of requested problem on system failure and life safety. Besides these two factors, the author proposed the importance of considering the energy efficiency and occupant satisfaction based on the former research for sustainability. This paper firstly tries to quantify the occupant satisfaction for normal daily maintenance requests which will provide the facility managers with suggestions on work prioritization. For a long time, it is a difficult task to quantify the occupant satisfaction, even though there are enough researches concerning the people satisfaction. In this research, author first designed a structured questionnaire including normal maintenance issues and they are measured by different factors such as thermal impact, acoustic impact, and so on. Then based on the classical disconfirmation theory, a framework was built to prioritize numerous works based on occupant satisfaction. For energy efficiency, due to the limitation of collecting real measured data, this paper referred the work from Lawrance Lab. They conducted the research to simulate the daily HVAC faults to quantify the energy impact through EnergyPlus, which provided the data of energy increase for some daily HVAC faults. An agent based model is proposed to both consider these two factors. Simulation was used to verify the framework and the result showed that the total satisfaction level and energy efficiency can be increased by 30% and 97% respectively.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/53601 |
| Date | 08 June 2015 |
| Creators | Cao, Yang |
| Contributors | Song, Xinyi |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Language | en_US |
| Detected Language | English |
| Type | Thesis |
| Format | application/pdf |
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