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FYPs/Thesis/Journal from Higher Education Institutions in Hong Kong
| Institution | Title | Type | Date | Author(s) | Abstract | Link |
|---|---|---|---|---|---|---|
| HKUST | Developing a Building Information Modeling Framework for Infrastructure Facility Management | FYP | 06/2015 | LO Tsz Fung TAM, Siu-hung |
There is a global trend of green buildings in recent years. The BEAM Plus green building standard developed by the Hong Kong Green Building Council (HKGBC) in 2009 has certified over 200 projects in Hong Kong. Green buildings have utilized various design features and operation technologies to reduce energy, waste and water consumption, improve indoor environmental quality and increase building performance. Facilities Management (FM) is the total management of all services that support the core businesses of an organization in a building. Nowadays, the design and structure of buildings are getting increasingly sophisticated and the need for specialization in management and maintaining them at high quality is vital. Facility managers have to acquire, integrate, edit, and update diverse facility information ranging from building elements, data, operational costs, room allocation, contract types, to maintenance. However, FM professionals have to face challenges resulting in cost and time related to productivity, efficiency and effectiveness losses. Building Information Modeling (BIM) seeks to integrate building lifecycle, provide improvements and help to overcome such those challenges. Thus, the aims of this project is to explore how BIM can contribute to and improve the FM profession and develop a BIM-based framework that facilitates the facility operations and management process of civil infrastructure facilities. To explore the technical feasibility of the proposed approach, It aim the Hong Kong University of Science and Technology Jockey Club Institute for Advance Study (IAS) as a target to implement and test, which is one of the world’s leading centers of research and intellectual inquiry, aiming to drive major advances and discoveries with its inter-disciplinary research locally and worldwide and establish itself as an international centre for excellence. For this purpose, the FM’s key tasks for indoor environmental quality improvement of green building features are identified and evaluated and a BIM model for the IAS building is developed and experimented by the FM tasks. As a result, such simulation helps shaping the vision, direction and policy for future energy and aviation systems. |
N.A. |
| HKUST | Developing a Building Information Modeling Framework for Facility Management | FYP | 06/2017 | LUK, Ka Yui TING, Hok Lam |
The sustainability of an infrastructure is of paramount importance to protect the benefits of both clients, engineers and its end-users. Building Information Modelling (BIM) therefore has become a vital tool for facility management (FM) to monitor the lifecycle of all building elements. Numerous of frameworks in the industry, however, are unable to locate and trace the asset information details of the building elements automatically for the asset management(AM) in the building lifecycle, especially the operation and maintenance stage. These existing frameworks highly rely on facility managers to locate the building elements and filter the information from a humongous database and carry out further data analysis for asset management strategies plan. Therefore, developing an integrated BIM framework to integrate the use of Radio Frequency Identification (RFID) technology and a FM software is essential for a more advanced facility management, especially the asset management performance of an infrastructure. In this research, AM is focused and a BIM model of the HKUST library is established as our targeted infrastructure for framework scenario establishment. Numbers of RFID tags have been installed on various library assets to collect respective RFID elements data. A Structured Query Language (SQL) database has been created to store in MySQL and integrate the data of the RFID tags with a FM software, Archibus. A RFID Asset Management website has been established to filter and visualize the required data. Finally, a BIM-based framework for asset management has been attained. The research framework has been applied to a HKUST Library-based AM scenario and the results have proved its AM functions and reliability in enhancing the AM performance of an infrastructure. |
N.A. |
| HKUST | Developing a BIM-Based Facility Management Framework for Building Operations | Report | 06/2017 | Zhang Zhongkuang Xin XIA |
Indoor air quality affects human comfort in several aspects such as temperature, humidity, CO2 and CO. With BIM and sensor technologies, the real-time indoor air quality data can be collected by sensors, transmitted and displayed in the BIM model, therefore the building control system can make appropriate adjustments to improve the indoor air quality. For BIM models, the model-based approach increases efficiency within individual organizations and truly shines during coordinated project delivery. Building information modeling can drive time and budget savings for building and infrastructure projects. For sensors, the data gathered is converted to a digital form and is processed at high speed. Sensor technology can store the data in memory, from where it can be retrieved later for processing, analysis and presentation. In this research, a plugin for grading the indoor air quality was designed, which can grade the indoor air quality at current or a specified past time as “good”, “fair” or “bad” showing in the BIM model. With the grading level, proper regulate and control could be made from the building control system to improve the indoor air quality. This designed plugin was used in a real case of seafront sport center in HKUST. Moreover, to efficiently manage sensors in a building, to reduce the energy consumption thus reduce the budget, linking facility and energy management to human comfort are also necessary and should be completed in the future work. |
N.A. |
| HKUST | Developing a BIM- and GIS-based Facility Management Framework for Underground Utilities | Report | 06/2017 | Starry Xing LI Liu YANG |
Nowadays there is a trend of integrating Building Information Modeling (BIM) and Geographic Information System (GIS) to develop the construction projects, including the projects of underground utilities. Compared with BIM and GIS, traditional utility management has plenty of limitations. Traditional utility management keeps 2D CAD drawings, which are separated by utility type and lack of surrounding information. Besides, it is difficult to find the specific utility pipe in 2D drawings under special situation. The working sequence arrangement for those pipes are sometimes not effective. This study aims to improve underground utility management in Hong Kong by using ArcGIS. The improvements consist of 3D visualization, querying and working sequence arrangement. 3D visualization of underground pipes and geological layers is created with reference to relevant Hong Kong standards and researches. Three cases are described to demonstrate the practical application of querying function. Working sequence of project in case 3 is analyzed through Excel. |
N.A. |
| HKU | Defining QS-BIM in Hong Kong | Thesis | 04/2019 | LEE Curtise | -- | N.A. |
| HKUST | Data-driven predictive maintenance planning framework for MEP components based on BIM and IoT using machine learning algorithms | Journal | 01/2020 | Cheng, J.C.P., Chen, W., Chen, K., and Wang, Q. | Facility managers usually conduct reactive maintenance or preventive maintenance strategies in building maintenance management. However, there are some limitations that reactive maintenance cannot prevent failure, and preventive maintenance cannot predict the future condition of MEP components and repair in advance to extend the lifetime of facilities. Therefore, this study aims to apply a predictive maintenance strategy with advanced technologies to overcome these limitations. Building information modeling (BIM) and Internet of Things (IoT) have the potential to improve the efficiency of facility maintenance management (FMM). Despite the significant efforts that have been made to apply BIM and IoT to the architecture, engineering, construction, and facility management (AEC/FM) industry, BIM and IoT integration for FMM is still at an initial stage. In order to provide a better maintenance strategy for building facilities, a data-driven predictive maintenance planning framework based on BIM and IoT technologies for FMM was developed, consisting of an information layer and an application layer. Data collection and data integration among the BIM models, FM system, and IoT network are undertaken in the information layer, while the application layer contains four modules to achieve predictive maintenance, namely: (1) condition monitoring and fault alarming module, (2) condition assessment module, (3) condition prediction module, and (4) maintenance planning module. Machine learning algorithms, ANN and SVM, are used to predict the future condition of MEP components. Furthermore, the developed framework was applied in an illustrative example to validate the feasibility of the approach. The results show that the constantly updated data obtained from the information layer together with the machine learning algorithms in the application layer can efficiently predict the future condition of MEP components for maintenance planning. | Link |