Data Quality Assessment of BIM Models for Facility Management

Building Information Modeling (BIM) consists of the creation of a digital representation of the physical and functional characteristics of a facility (National Institute of Building Sciences, 2015b). As an integrated database of coordinated, consistent, and computable information (Ramesh, 2016), BIM can drastically improve the quality of construction projects by bringing together technology, process improvements and digital information (Fallon et al., 2007).

BIM-models include objects whose properties describe geometrical dimensions, materials, finishes, specifications, manufacturer, price, and also relationships with other objects, such as the location of the objects within rooms of the facility (ADEB-VBA, 2015). Additionally, since BIM information is reused throughout the lifecycle as a single source of truth, it results in less errors and greater consistency, clarity, and accuracy (Kivits & Furneaux, 2013). Provided that BIM capabilities are correctly exploited and explicitly defined, BIM enables improved collaboration between designers, engineers, constructors, and facility managers across the life cycle (Kivits et al., 2013), which results in maximized efficiency, improved information exchanges, and a reduction of costs (Vega Völk, 2017).

This is why many governmental and public organizations (e.g., Smithsonian, 2018; Société Québécoise des Infrastructures, 2016; The Ohio State University, 2019a; US Department of Veterans Affairs, 2017a) have started to mandate the use of BIM for new projects to improve productivity and information management.

According to the NIST (Gallaher et al., 2004), the major benefit of BIM lies in the crossplatform interoperability it offers for data transfer and its ability to centralize asset management information. The report identifies a current lack of integration between project management (PM) and asset management (AM) and sees the lack of information capture and transfer as one of the main reasons why owners are unable to carry out proper maintenance activities. The objectives, operation modes, disciplines and practices associated with PM and AM differ in several aspects (IAM, 2015), mainly due to the fact that the project (temporary) is traditionally separated from the operation (permanent).

BIM has thus far mainly been used in the design and construction phases (Heaton et al., 2019). However, major benefits could be obtained during the Operation and Maintenance (O&M) phase by improving various processes (Motamedi et al., 2018) and providing a repository of detailed information of the built asset. BIM can be used during operations to populate facility operations databases with both geometry and parameters, thus supporting information technology used by owners’ organizations (Pishdad-Bozorgi et al., 2018). Other useful features provided by BIM for O&M are visual information on the location of assets, relationships between these assets, and a history of maintenance activities (Motamedi et al., 2014).

Given that BIM can be used for O&M, an increasing number of owners would like to have complete and useful BIM models at the end of the construction project (Becerik-Gerber et al., 2012). However, while the commissioning and handover processes of delivering physical assets is very well defined, there is a lack of standards, guidelines, or procedures for digital project delivery. This makes it difficult for owners to, for instance, defining deliverables (Thabet & Lucas, 2017).

Operations & Maintenance, Asset Management, Facility Management

Facilities Operations and Maintenance 

Since the O&M phase accounts for the largest proportion of assets lifecycle costs (50–70% of the total annual operating costs, and 85% of the entire life cycle costs), effective management is crucial to obtain significant financial benefits (ABAB, 2018).

Asset Management is the coordinated activity of an organization to realize value from assets over the entire lifecycle. This is achieved by balancing costs, opportunities and risks against desired asset performance, technical and financial decisions aim to fulfill organizational objectives (Heaton et al., 2019). Facility Management, on the other hand, regroups various daily services to ensure functionality of the built environment by integrating people, place, process and technology (Ramesh, 2016). Among others, FM aims to provide safe and efficient environment for facility occupants by tracking facility components accurately, identify inefficiencies in building operations, and respond quickly to client requests (GSA, 2011).

Facility Information 

AM and FM activities depend on the accuracy and accessibility of data created in the design and construction phases and updated throughout the O&M phase (GSA, 2011). Thus, information should be managed and analyzed in a structured and systematic way to facilitate decision-making.

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A lack of information can result in cost overruns, inefficient building operations, and untimely resolution of client requests. Unfortunately, an owner’s decision making often relies on a range of incomplete, inaccurate, or vaguely defined information leading to poor decisions Parsanezhad & Dimyadi, 2014).

On the other hand, an overload of information may saturate an operation’s database and decrease its efficiency. Additionally, excessive unorganized information in non standard formats can simply become unused data (Lu, 2018). Defining and formalizing the required useful FM information before the design of an asset is the key to effective management of this vast quantity of information, which is critical to the success of facility operations (Lu, 2018).

Another issue is that designers and constructors seldom know what information is needed for the FM. Thus, the owner’s input and requirements should be sought out at the initial stages of the project (Masania, 2015). However, most owners do not have precise requirements for information deliverable to ensure the usefulness of the closeout information (Liu & Issa, 2013).

Issues with Static Documentation

Facility Information is often delivered through static documents (e.g. CAD, PDF), which often do not leverage the potential benefits of digital technologies (ABAB, 2018). These static documents raise issues at the time of handover and throughout the O&M phase, such as manual search and retrieval of information and failure to carry-out any kind of data verification (Lu, 2018). Additional issues of static data include its low quality, the complexity of its organization, the search time-cost, and storage of paper documents (Whyte et al., 2010).

This issue of static data could be addressed by more precise guidelines regarding the delivery and use of standardized BIM information for O&M (Lu, 2018). Indeed, aside from 3D geometry, BIM can supply centralized and standardized assets and spaces data to FM databases to be used for activities such as maintenance and renovation planning (Akcamete et al., 2010).

Table des matières

INTRODUCTION
CHAPTER 1 LITERATURE REVIEW
1.1 Operations & Maintenance, Asset Management, Facility Management
1.1.1 Facilities Operations and Maintenance
1.1.2 Facility Information
1.1.3 Issues with Static Documentation
1.2 BIM for Operations
1.2.1 Facility Management Systems
1.2.2 Enabling BIM for the O&M Phase
1.2.3 FM-BIM Creation and Model Evolution
1.2.4 Updating FM Data
1.3 BIM Information Requirements in the Industry
1.3.1 Information Requirements Types
1.3.2 Examples of Information Requirements Documentation
1.4 BIM Data Quality Assurance and Control
1.4.1 Definitions
1.4.2 BIM Models Quality Issues
1.4.3 Planning Quality Assurance
1.4.4 Executing Quality Control
1.4.5 Quality Control Checklists and Automated Tools
1.5 Interoperability
1.5.1 Definition and Opportunities
1.5.2 Industry Foundation Classes (IFC)
1.5.3 Construction Operations Building information exchange (COBie)
1.6 Chapter Summary and Research Gaps
1.6.1 Facility Management and BIM for Operations
1.6.2 Requirements Identification and Compliance Monitoring
1.6.3 BIM Data Quality Assurance and Quality Control
1.6.4 Interoperability
CHAPTER 2 RESEARCH METHODOLOGY AND PROPOSED SOLUTION
2.1 Research methodology: Design Science Research
2.1.1 Research steps
2.1.2 Data collection methods and validation approach
2.2 Proposed Framework for FM-BIM Quality Management
2.2.1 Documents and requirements relationships
2.2.2 Stakeholders’ roles and responsibilities
2.2.3 Quality Management Process Flow
2.3 Proposed Checklist for Model Quality Control and Clean Up
2.4 Proposed Quality Control Process Flow
2.5 Chapter Summary
CHAPTER 3 DEVELOPING AND IMPLEMENTING QM TOOLS
3.1 Software Used
3.2 Customization of tools
3.3 Development of Software Tools for Specific Quality Control Items
3.4 Development of a QM Dashboard
3.5 Chapter Summary
CHAPTER 4 CASE STUDIES: BIM QUALITY MANAGEMENT
4.1 University Campus Expansion Project
4.1.1 Project Presentation
4.1.2 Implementation of the Quality Management Process
4.1.3 Assessing the Efficiency of Developed Tools
4.1.4 Addressing missing requirements
4.1.5 Upcoming opportunities
4.2 Care Center Project
4.2.1 Project presentation
4.2.2 FM-Platform and COBie Mandate
4.2.3 Identified Issues
4.2.4 Application of the Proposed Methods
4.2.5 Adapting the Proposed QC Tools and Processes for COBie Deliverables
4.2.6 Evaluation of results
CHAPTER 5 DISCUSSION
CONCLUSION

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