Building an ontological knowledgebase for bridge maintenance

The operation stage has the biggest potential value in the bridge life cycle management, and it often critically influences the overall cost of the bridge. As such, changes in the efficiency of the project's operation stage could be of significant benefit to the overall project. However, current approaches in the operation stage often lack the effective support of computer-aided tools. This research presents a holistic method based on an ontology to achieve automatic rule checking and improve the management and communication of knowledge related to bridge maintenance. The developed ontology can also facilitate a smarter decision-making process for bridge management by informing engineers of choices with different considerations. Three approaches; semantic validation, syntactical validation, and case study validation, have been adopted to evaluate this ontology and demonstrate how the developed ontology can be used by engineers when dealing with different issues. The results showed that this approach can create a holistic knowledge base that can integrate various domain knowledge to enable bridge engineers to make more comprehensive decisions rather than a single objective-targeted delivery

A BIM-based value for money assessment in public-private partnership: an overall review

Public-private partnerships (PPPs) have proliferated and adapted to public development in recent decades; within it, the value for money (VfM) assessment defines the feasibility of the project procurement model as one of the essential components of PPP. However, evaluating the VfM in PPPs remains problematic. Given concerns about PPP profitability, a more integrated VfM evaluation is urgently needed to manage multiple indicators along the project lifecycle. Building information management (BIM), popular in architecture, engineering, and construction, provides resources that could support the VfM to a great extent. This paper uses a review approach to identify the current issues that are affecting VfM assessments and suggests that BIM, functioning throughout the PPP lifecycle, could support decision-making in VfM processes in order to satisfy service targets

Knowledge management in PPP decision making concerning value for money assessment

Public-private partnership (PPP) is the current procurement model used for largescale public engineering and municipal facilities procurement and is now advocated by governments around the world. Value for money (VfM) assessment is a critical process used to evaluate whether the PPP procurement model applies to a project throughout its lifecycle. VfM assessment aligns with financial capacity assessment and feasibility assessment, providing an essential decision-making reference for project managers and associated with performance measurement (PM) in the ex-post stages, which are linked to the payment model. Therefore, the evaluation of the project through VfM determines the success of the PPP model to a great extent. Through a comprehensive literature review, the dissertation identifies the practical deficiencies for the current VfM assessment process and presents a detailed view of the content of the VfM assessment. Based on that, the dissertation determines the research motivation and formulates detailed research questions and hypotheses to establish a thorough understanding of a knowledge-based management platform to achieve automated processes that support human decision making. By using the deductive approach, this research leverages knowledge engineering principles and developed a core VfM knowledge base to help manage knowledge in the PPP decision-making process concerning VfM assessment. The system development is based on the design science methodology. In order to integrate information about the engineering project management and VfM assessment, the standardized information exchange processes are first used to develop robust information with project versatility. The Building Information Modelling (BIM) application platform, which uses Industry Foundation Classes (IFC) as the engineering project data source, is connected with the developed information schema, thus establishing the basis for implementing automated information exchange. Second, ontology modeling is used to establish a VfM knowledge base. The various factors associated with the PPP project can be stored in a semantic environment for better identification by engineers. Furthermore, automated project assessment is achieved by developing different rules-based functions in the ontology and combining them with the data platform represented by BIM. By using case studies and action research strategies, this research demonstrates the feasibility of the constructed knowledge base. Abstract iv The main outcomes of the research lie on the definition and screening of information for VfM assessment, as well as the establishment and application of a smart knowledge base. The developed components and software tools have been thoroughly tested, validated and calibrated by leveraging knowledge from experienced domain experts, software companies and other industry partners. Due to the generic development principles adopted in the research, the method, tools and framework can be further extended for other related areas where smart decision making is require

Knowledge management in construction health and safety based on ontology modeling

Knowledge management in construction health and safety is an intensive process involving different stakeholders. However, this domain’s information is still fragmented and stored in various disordered formats that require systematic structure for reusing and sharing. This study aims to develop a domain ontology, HSM-Onto (Health and Safety Management-Ontology), to construct health and safety knowledge and improve health and safety management decision making. The HSM-Onto could implement the organization, storage and reuse of construction health and safety knowledge. It comprises two primary domain knowledge contexts, including construction project context and risk context. Based on the conducted analyses, the findings show that the HSM-Onto’s health and safety knowledge sharing is effective and equips health and safety employees with sound recommendations for decision making

Knowledge-based OpenBIM data exchange for building design

Building design is highly complex as it involves numerous professionals and their interactions, hence with diverse tools used and multi-resources and different structured data and information required to be processed. Despite the existing efforts to develop multi-objective decision making tools to support complex design, most of the research face difficulties to provide holistic, dynamic and collaborative knowledge base due to the complexity of the information interoperability issues across different parties and throughout life cycle. This paper developed an automatic data exchange framework that combines only the necessary data from BIM models using semantic web technology to eliminate inefficiencies in data exchange and improve decision-making early in the design stage. The proposed data acquisition method can produce a dynamic knowledge base to connect both static and dynamic information. A multi-objective knowledge base was developed to assist engineers associated with sustainability and cost in comparing different design options based on the existing BIM data. The proposed ontology was developed using a machine-readable format, allowing the ability to add more concepts to it in the future and work with other automated tools. The validated framework could reduce human involvement and errors while providing more efficient ways to leverage diverse information sources together to support holistic decision-making for building design

An ontology-based approach supporting holistic structural design with the consideration of safety, environmental impact and cost

Early stage decision-making for structural design critically influences the overall cost and environmental performance of buildings and infrastructure. However, the current approach often fails to consider the multi-perspectives of structural design, such as safety, environmental issues and cost in a comprehensive way. This paper presents a holistic approach based on knowledge processing (ontology) to facilitate a smarter decision-making process for early design stage by informing designers of the environmental impact and cost along with safety considerations. The approach can give a reasoning based quantitative understanding of how the design alternatives using different concrete materials can affect the ultimate overall performance. Embodied CO2 and cost are both considered along with safety criteria as indicative multi-perspectives to demonstrate the novelty of the approach. A case study of a concrete structural frame is used to explain how the proposed method can be used by structural designers when taking multi performance criteria into account. The major contribution of the paper lies on the creation of a holistic knowledge base which links through different knowledge across sectors to enable the structural engineer to come up with much more comprehensive decisions instead of individual single objective targeted delivery

A theoretical holistic decision-making framework supporting collaborative design based on common data analysis (CDA) method

The enormous expansion of information, which is assembled from various design tools, has caused challenges in data exchange and compelled companies to find various solutions to improve collaboration. Data exchange within Building Information Modelling (BIM) context has been mainly focused on individual disciplines. Even though several attempts have been made to develop data exchange requirements for BIM models, there is still a lack of homogeneity since no method for classifying and sharing those requirements is clearly outlined. A clearly defined “single truth of information” is still not acknowledged yet. Software tools require unambiguous clarity of the semantics, which can help various stakeholders to proceed with their design tasks. However, there is still a lack of multi-dimensional knowledgebase for holistic decision-making within a BIM workflow. Therefore, this paper presents a common data analysis (CDA) referencing various concepts such as the standardised Information Delivery Manual (IDM) method, model view definition (MVD) and the concept of semantic intersection to conclude “single truth of information” and “partial truth of information” data sets that form the basis for a theoretical holistic decision-making framework to support collaborative design. The information defined in this research was validated based on existing resources and literature. Following the concluded data sets, a model can be transformed automatically at the minimum commonality level, creating a starting point for other professions. Following the analysis, a theoretical holistic decision-making framework was proposed. The innovation of the proposed framework lies in providing a holistic decision-making system that combines both data extraction using the concluded data sets and semantic web technology to eliminate inefficiencies in data sharing and improve the decision-making process in the early design stage by providing the stakeholders with rational solutions with less effort and time. This paper provides the essential requirement for a holistic decision framework from a data processing perspective

Towards future BIM technology innovations: a bibliometric analysis of the literature

The evolution of the construction industry is associated with the continuous implementation of new technologies. Building Information Modelling (BIM) has revolutionised the collaboration and data sharing processes in the architecture, engineering, and construction (AEC) industry. However, it needs to be supported by new technologies that can embrace digital construction by transforming the construction industry into a dynamic environment. There is a lack of understanding of the cutting-edge technologies that have emerged to help with the digital transformation of the construction industry. There is a need to understand all these technologies and how they can be leveraged holistically towards future BIM innovations. Therefore, this article conducts a literature review to evaluate how targeted cutting-edge technologies can be utilised to release the full potential of BIM from a technical perspective. A bibliometric analysis focusing on the co-occurrence of keywords related to various technologies, their links with BIM, and their related research themes was conducted based on the Web of Science (WoS) database holdings from 2010 to 2019. The findings demonstrate that one type of technology can help with solving a specific issue. However, using one technology alone does not solve an issue entirely. The current technology has been utilised independently and not as a coherent system. Thus, a weak information integration and management approach can restrict the leveraging of a smart BIM environment. This paper is not meant to be exclusive. Many new technologies, concepts, and ideas can be added to help realise BIM potentials that are not covered in this study. Furthermore, the analysis was based on the dataset retrieved from WoS and only included the literature in English. Based on those findings, the authors indicated a technology fusion to support BIM development

Developing a framework leveraging building information modelling to validate fire emergency evacuation

In fire emergency management, a delayed execution will cause a significant number of casualties. Conventional fire drills typically only identify a certain percentage of evacuation bottlenecks after the building has been constructed, which is hard to improve. This paper proposes an innovative framework to validate fire emergency evacuation at the early design stage. According to the experience and knowledge of fire emergency evacuation design, the proposed framework also introduces a seamless two-way information channel to embed fire emergency evacuation simulations into a BIM-based design environment. Several critical factors for fire evacuation have been reviewed in relevant domain knowledge, which is used to build virtual characters to test in experimental scenarios. The results are analyzed to validate fire emergency evacuation factors, and the feedback knowledge is stored as a knowledge model for further applications