International Construction Specialty Conference of the Canadian Society for Civil Engineering (ICSC) (5th : 2015)

Review of BIM quality assessment approaches for facility management Zadeh, Puyan A.; Staub-French, Sheryl; Pottinger, Rachel Jun 30, 2015

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5th International/11th Construction Specialty Conference 5e International/11e Conférence spécialisée sur la construction    Vancouver, British Columbia June 8 to June 10, 2015 / 8 juin au 10 juin 2015   REVIEW OF BIM QUALITY ASSESSMENT APPROACHES FOR FACILITY MANAGEMENT Puyan A. Zadeh1, 3, Sheryl Staub-French1 and Rachel Pottinger2 1 Department of Civil Engineering, University of British Columbia, Canada 2 Department of Computer Science, University of British Columbia, Canada 3 p.zadeh@civil.ubc.ca  Abstract: Assessing the quality of information in building information models (BIM) at the time of project handover is critical for owners. Lack of quality information in delivered BIMs can cause significant issues in using BIM for facility management purposes, potentially limiting or preventing their use in building operations. Our studies of numerous BIM projects and deliverables have found that most BIMs created for design and construction today contain significant quality issues including inaccurate, incomplete, or unnecessary information. To make these models useful for building operations requires significant adjustment to the models, which can be very time-consuming and costly. This paper describes different types of quality issues identified through numerous case studies of BIM projects and categorizes them according to different model perspectives (entity, model, and user level) and relevant facility management perspectives (assets, MEP systems, and spaces). We identify the different characteristics of each type of quality issue and then systematically analyze relevant literature in the AEC and computer science domains to put these issues in context. This analysis highlights the ambiguity in characterizing information quality issues in a BIM and demonstrates the need for a comprehensive and consistent formalization of BIM quality. 1 INTRODUCTION Assessing the information quality (IQ) of building information models (BIM) for facility management (FM) purposes is a critical and challenging task for owners at the time of project handover. Lack of IQ in delivered BIM could have costly consequences for owners, including: manual adjustments to correct and complete the models; laser-scanning of (a part of) the building and related post processing efforts; and delays in the start of FM systems. Currently, researchers and owner organizations have different perspectives about the IQ of BIM, which consequently lead to different approaches to its assessment. Although organizations like U.S. General Services Administration (GSA) and British Standards Institution (BSI) have developed approaches to enforce BIM requirements throughout the project handover (BSI 2014, GSA 2011), such approaches are mainly based on generic checks and do not cover all required IQ characteristics for FM needs. For proper BIM-IQ assessment, it is necessary for owners to have a clear understanding about “what” are the potential quality issues, “which” IQ characteristics are relevant, and “how” to assess them. The objective of this paper is to contribute to the development of a comprehensive and consistent representation of BIM quality for owners. Through numerous case studies of BIM projects and interviews with FM personnel, we describe different types of quality issues and categorize them according to 342-1 different model perspectives (entity, model, and user level) and relevant facility management perspectives (assets, MEP systems, and spaces) in section 2. In section 3, we identify the different characteristics of each type of quality issue and then systematically analyze relevant literature in the AEC and computer science domains. This analysis highlights the ambiguity in characterizing information quality issues in a BIM, demonstrating the need for a comprehensive and consistent formalization of BIM quality for owners.  2 BIM QUALITY ANALYSIS FRAMEWORK FOR FM The motivation of this study has its roots in numerous case studies of BIM project deliverables and interviews with various FM personnel. In order to systematically analyze the different types of BIM quality issues, we developed an analysis framework considering different FM categories and model analysis perspectives (Table 1). Generally, FM information management systems (IMS) require information related to three essential terms: assets, MEP systems, i.e., mechanical, electrical, and plumbing/piping, as well as spaces. Although MEP systems may be considered a compilation of different assets, there are still differences between asset related and MEP system related IQ issues. Therefore, we divided the observed IQ issues accordingly in terms of assets, MEP systems, and spaces. Furthermore, the BIM-IQ issues can be categorized into different types from different analysis perspectives of model consumption. We determine these perspectives as: 1) entity level, which focuses on the smallest information pieces in a model; 2) model level, which considers the entire BIM as one information package; and 3) user level, which analyzes the information system from the model user’s perspective.  Table 1: BIM-IQ analysis framework for FM The analysis methodology below follows the structure of this framework. Specifically, we go through each issue type to analyze them systematically in correspondence with the related FM category. As the first step of the systematic analysis, we briefly describe each issue type by giving specific examples from a case study project. This description includes the IQ characteristics that are affected as well as their relevance for FM. In the next analysis step, we discuss the relevant literature for each type of quality issue. This includes the terms used by researchers to address these issues, the general topic that they discuss and their proposed approaches for preventing (IQ assurance) or identifying (IQ assessment) such issues. Finally, we evaluate these different perspectives and discuss the potential research gaps for each issue type. 3 TYPES OF QUALITY ISSUES AND RELEVANT LITERATURE This section presents a systematic analysis of each type of BIM quality issue from the BIM-IQ analysis framework introduced above in Table 1. In this analysis, we start with the entity level perspective and discuss the issue types related to assets, MEP systems, and spaces, and then continue with the model and user level perspectives.  BIM-IQ Perspectives FM Categories Entity Level Model Level User Level Asset Incomplete Assets  (Table 2) Inaccurate Values for Asset Attributes (Table 4) Inaccurate Asset Placement (Table 6) Compliance with BIM Standards (Table 8) Model Clashes Understand-ability of Information MEP Systems Incomplete MEP Systems (Table 3) Inaccurate Values for System Definitions (Figure 4) Inaccurate Spatial Allocation of MEP Systems (Table 7) Space Incomplete Spaces Inaccurate Values for Space Definitions (Table 5) Inaccurate Space Placement Issue Type Categories: Information Incompleteness (sec.  3.1) Value Inaccuracy (sec. 3.2 ) Spatial Inaccuracy (sec.  3.3) Model Incompatibility (sec.  3.4) Uncoordinated Information Incomprehens-ible Information 342-2 (2006). This list follows an object-oriented approach and so provides a hierarchy for each asset type that can have up to seven levels. The examples above and the similar references (GSA 2011, Kulusjärvi 2012, National Institute of Building Sciences 2007, SBCA 2013) show that the main focus of the AEC researchers regarding to the information completeness is on the IQ assurance by using one of the introduced methods above. However, significant issues remain in terms of how to deal with the incomplete models, how to incorporate such checklists and hierarchies and integrate them into the owner’s requirements and how to assess them in a given BIM. Incomplete MEP Systems: It is necessary for FM-IMS to define MEP systems completely in the mechanical BIM (GSA 2011, Kulusjärvi 2012, SBCA 2013, USC 2012). However, our analysis of BIM projects demonstrates that MEP systems are frequently defined inaccurately and incompletely in the mechanical BIM as in our case study (Table 3). This type of IQ issue is very similar to the incompleteness of assets with the difference that in this case one should investigate the entire components of a system or a sub-system. Table 3: Incompleteness of system definitions in BIM The information about systems is especially significant for intelligent troubleshooting processes where one does not exactly know which equipment is not working properly as well as for better understanding the consequences when an asset is broken. The completeness check for MEP systems should include the identification of assets without a specific system as well as systems that miss a major asset as a member (either the major asset is not modeled or it is not assigned to the system). As shown in Table 3, even though this IQ issue type and its consequences for the projects are not explicitly discussed in detail among AEC researchers yet, there are few (but important) references that propose IQ assurance approaches to avoid incompleteness in the MEP system definitions. Nevertheless, there is a research demand for evaluation of the assurance methods, and for the assessment of the required system attributes and the relevant system components (assets). Incomplete Spaces: In addition to assets and systems, spaces play also a crucial role in an FM-IMS. The representation of spaces in a BIM can support FM personnel particularly for what-if analyses, decision-making sessions, and routing the service components (Akcamete et al. 2010, Becerik-Gerber et al. 2011, Nepal et al. 2012). However, incomplete space information makes such processes more difficult. Researchers treat incompleteness of spaces in BIMs as an obvious issue that should be addressed. Therefore, this issue type has not been discussed as a separate topic yet and its assessment is usually included together with other building entities as a part of general checks, as in (Kulusjärvi 2012, LACCD BIMS 2010, National Institute of Building Sciences 2007, SBCA 2013, USC 2012).  Short description Identifying the missing MEP system components  Example  Figure 2: The piping system is incomplete for the mechanical room our case study # Used Term General Discussion Topic Assessment / Assurance Used Method Reference Domain 1 – Required BIM objects and properties Assurance Checklist (GSA 2011) AEC 2 – System BIM Assurance Checklist (Kulusjärvi 2012) AEC 3 – MEP Quality Assurance Assurance Checklist (SBCA 2013) AEC 4 – MEPF Specifications Assurance Checklist (USC 2012) AEC 5 – – Assurance COBie (BIM Task Group 2012) AEC (a) BIM (b) As-is 342-4 3.2 Value Inaccuracy (Entity Level) Inaccurate Values for Asset Attributes: In a desired BIM for FM, it is significant that the major assets are defined accurately. That means that the modeled assets must have the required attributes with precise values, their type must be correct and they need to be represented in the model with the correct size. In addition, the asset names must be clear, meaningful and not redundant. Inaccuracies in the attribute values is a very common IQ issue that we also recognized in our observations (Table 4).  Table 4: Inaccurate definition of modeled assets Reviewing related literature shows that when AEC researchers discuss the quality of BIMs, they strongly connect it to the accuracy aspect of the IQ and mainly use this term to address IQ characteristics related to the modeled “values”. However, much of the reviewed literature either does not specifically describe their interpretation of this term in more detail, as in (Du et al. 2014, GSA 2011, Kasprzak et al., National Institute of Building Sciences 2007), or the literature describes it in different ways. For example, (Berard 2012) refers to accuracy through different terms like information “precision”, “unambiguity” and “level of detail.” Du et al. (2014) define information accuracy as the degree to which the BIM models precisely reflect the physical real world conditions of a project. (Kulusjärvi 2012) address the accuracy aspect of IQ through the term “correctness.” These examples highlight a certain degree of ambiguity among AEC researchers when they discuss the quality values in a model. In contrast to the AEC researchers, the CS researchers organize these aspects in a different way. For example, (Lee et al. 2002) assign all value-related IQ aspects to the “intrinsic” IQ category. This category covers aspects like correctness, Short description Major assets must have the required attributes with precise values, their type must be correct and they need to be represented in the model at the right place with the correct size. Example  Figure 3: Example of inaccurate information for heat pump #03  # Used Term General Discussion Topic Assessment / Assurance Used Method Reference Domain 1 Accuracy Compliance and Submittals – – (GSA 2011) AEC 2 Accuracy Value of Information for Facilities Management Assessment – (Kasprzak et al.) AEC 3 Unambiguity and Level of Detail Precision Assessment Survey (Berard 2012) AEC 4 Accuracy Quality Assurance Assurance Checklist (SBCA 2013) AEC 5 Accuracy Data and Process Requirements Assurance Checklist (Becerik-Gerber et al. 2011) AEC 6 Accuracy Minimum BIM Assurance – (National Institute of Building Sciences 2007) AEC 7 Accuracy BIM Performance Assessment Quantity Takeoff (Du et al. 2014)  AEC 8 Correctness Quality Assurance Assurance – (Kulusjärvi 2012) AEC 9 Accuracy Quality of Raw Data – – (Assaf and Senart 2012) CS 10 Accuracy Data Quality – – (Olson 2002) CS 11 Accuracy and Precision Data Quality Dimensions – – (Wand and Wang 1996) CS 342-5 unambiguous, consistency, precision, reliability, etc. which match mostly with the different interpretations of accuracy in the AEC domain. Nevertheless, there is still a great potential for unambiguous analysis of each of these aspects. In addition, Table 4 shows that the researcher mainly focus on using checklist for accuracy assurance and assessment methods. However, using checklists is a very generic approach and leaves room for different interpretations.  Inaccurate Values for System Definitions: In contrast to the completeness of MEP systems, the accuracy of system definitions has not been discussed explicitly in the AEC literature yet. The main reason is that such systems can be considered as a composition of different assets (as system components) and so the value accuracy of asset’ attributes can result in a certain level of accuracy for the related system. Thus, the values of important system attributes can be calculated as summations of related asset attributes, as for system flow, total pressure, electricity voltage, medium type, etc. Therefore, most of the BIM authoring tools offer automated calculations for system attributes. Nevertheless, there are system attributes that describe specifically a system without a direct connection to the system components (Figure 5), like system names, types, classifications, and related documents (specs, sequence of operation, etc.). Thus, this IQ issue type has a high potential for further research to identify the consequences of inaccurate system information for FM-IMSs. Inaccurate Values for Space Definitions: Unlike incompleteness of spaces (and similar to other value inaccuracy issues discussed above), AEC researchers put emphasis on IQ of space definitions. Figure 5(a) in Table 5 shows an example from our case study where the space definition in BIM is inaccurate and incomplete. Figure 5(b) shows how building operation personnel keeps track of changes in the space arrangement with the help of printed PDF floor plans. The space related inaccuracies in the architectural BIM include spaces with incorrect utilization as well as spaces with different names from the actual space names in the building. A similar space related issue is the compliance of the room names with a required nomenclature by the owner. Such compliance is also documented in (Kulusjärvi 2012, LACCD BIMS 2010, National Institute of Building Sciences 2007, SBCA 2013, USC 2012).  Table 5: Inaccurate definition of modeled spaces in BIM Short description Identifying the inaccuracy in space definitions Example  (a) BIM (b) As-Is Figure 5: Inaccuracy and incompleteness in space definitions CIRS architectural BIM # Used Term General Discussion Topic Assessment / Assurance Used Method Reference Domain 1 – Spatial BIM Assurance Checklist (Kulusjärvi 2012) AEC 2 – Space Validation  Assurance COBie (USC 2012) AEC 3 Space Requirements Modelling Requirements Assurance Checklist (LACCD BIMS 2010) AEC 4 – Quality Assurance Assurance Checklist (SBCA 2013) AEC 5 Space Management Data Requirements for FM – – (Becerik-Gerber et al. 2011) AEC Figure 4: Inaccurately defined system attributes for an air terminal in our case study 342-6 3.3 Spatial Inaccuracy (Entity Level) This IQ issue category is about the inaccuracies in placing the entities in a three-dimensional environment as in BIM. This group of issue types is significant because the spatial placement of entities brings the architectural and mechanical information hierarchies together. Inaccurate Asset Placement: For facility operations, it is very important to find the related spaces for different assets (Asen et al. 2012). Becerik-Gerber et al. (2011) and Cotts et al. (2009) suggest facility managers ensure that the trade mechanics are familiar with equipment location. This highlights the significance of trades’ personal experiences with a facility where an intelligent FM-IMS is not available. Hence, using BIM could be a suitable alternative approach through accurate placements of assets in spaces. This requires both the accurate space definition as well as accurate asset placement in the space according to a spatial hierarchy. This placement is not only about identifying in which space is an asset located but also it is about determining where exactly this asset is placed in the assigned space. Table 6: Asset placement Finding assets’ exact location is challenging in projects without an as-built model, as in our case study. The reasons are first, mechanical and architectural models are usually separate models and need to be merged and adjusted, and second, it is challenging to assign assets correctly within a wall or ceiling to a space in an automated way. For instance, the height of a room begins from the top of the floor to bottom of the ceiling. Therefore, the challenge is to find the correct space for the assets within the floors’ slab. Figure 6 in Table 6 shows an example of assets within a second floor slab that belong either to the upper space (like diffusers) or to the space below (like light fixtures). Inaccuracy in asset placement in BIMs is a significant issue for creating FM-IMSs. Reviewing related literature shows that this IQ issue type is only marginally addressed in few publications and general expectation is that modelers assure the accuracy of asset-space relation by using a list of certain generic measures. However, a clear IQ assessment approach in this connection is missing. Inaccurate Spatial Allocation of MEP Systems: The relationship between MEP systems and spaces must include both the actual location of system components (assets) in the building as well as the served spaces by each MEP system. This is also emphasized in (Asen et al. 2012) where they describe such relationships as “spatial” for physical relation between assets/systems and spaces, and as “logical” for non-physically related assets/systems and spaces. The spatial relationship between MEP systems and spaces can be considered as a summation of space assignments for individual system components (assets). Thus, through an accurate system definition and correct placement of assets in spaces, this kind of issues can be avoided. The logical relation corresponds to the identification of which space(s) are served through a system (Table 7). This is significant for systems with a central role in a building, which usually serve spaces (mechanical zones) other than the location of their major assets. Short description Identifying the location of assets in BIM, i.e., the suitable space and the correct position in the space Example  Figure 6: Assets within the floor slab of CIRS, including pipes, radiant heaters and light fixtures # Used Term General Discussion Topic Assessment / Assurance Used Method Reference Domain 1 Spatial relationship Visual Analytics for FM – – (Asen et al. 2012) AEC 2 – Quality Assurance Assurance Checklist (SBCA 2013) AEC 3 Spatial BIM BIM Requirements Assurance Checklist (Kulusjärvi 2012) AEC 342-7 Table 7: Spatial allocation of MEP systems Identification of served spaces is very relevant for FM (East et al. 2013, GSA 2011, Teicholz 2013, USC 2012), since such significant systems usually require frequent maintenance and the buildings operators need to know which building parts are affected when a system needs to be maintained. Automated identification of served spaces for MEP systems is more complicated than the location finding challenge above. Our review of related literature in Table 7 reveals that in the discussion about spatial allocation of MEP systems, researchers have been focused so far on the quality assessment measures for BIM mainly using COBie spreadsheets. 3.4 Model Incompatibility (Model Level) Model incompatibility is about the model compliance with BIM standards and is an important IQ issue type from the model level perspective (Table 8). This issue type is about whether or not the information within the model is compatible with specific data structures. In other words, this issue type corresponds to the way the information is organized in BIM and it is related to all FM categories (assets, MEP systems and spaces). This is an important IQ characteristic, since the compliance with a standardized data structure, such as IFC, can shape the modeling process, facilitate information exchange between different BIM authoring tools and as a result can increase the quality of collaboration in a project (Kulusjärvi 2012, LACCD BIMS 2010). In addition to IFC standards, some literature propose the use of BIM exchange standards (like COBie) as alternative benchmarks for model compatibility assessments. For instance, the authors in (East et al. 2013, Kasprzak et al., Teicholz 2013, USC 2012) suggest to perform compatibility checks with COBie standard worksheets as a quality control approach. Moreover, the authors in (USC 2012) propose the compatibility checks with EcoDomus as an alternative to COBie for IQ control purposes. Our literature review results that AEC researchers have comprehensively researched model compatibility with BIM standards (Table 8). However, they address it through very different terms. For example, the authors in (Kasprzak et al.) describe it as “Data & Process Standardization” and propose that the modeled information should be in compliance with specific standards, like the internal standards of the Office of Physical Plant (OPP) at the Pennsylvania State University. This approach is similar to the “Quality Control” checks that the authors in (Messner and Kreirder 2013) demand as a part of owner requirements. (Schuette and Rotthowe 1998) address the validation of an information system as the “Language Adequacy” of the model. This emphasizes the importance of this IQ aspect, i.e., the information structure as the “grammar” for organizing data, for the researchers before the BIM era. An alternative approach to check the validation of model data structure is to analyze the warnings that specific BIM artifacts report as described in (Du et al. 2014, USC 2012). An extensive analysis about the warning messages in BIM artefacts is given in (Lee et al. 2015). They divide these warnings into three categories: annotation, information and geometry warnings. The interesting point about such researches is that they do not only propose approaches for assessing IQ issues but also provide analyses to identify the reason of those warnings, which makes this type of researches more valuable. Short description Identifying the spaces that are served by MEP system  Examples  Figure 7: Air Handling Units (AHUs) that are located in the basement serve different spaces in the building # Used Term General Discussion Topic Assessment / Assurance Used Method Reference Domain 1 Served zones FM Handover Model Assessment COBie (East et al. 2013) AEC 2 Served area BIm for FM – – (GSA 2011) AEC 3 Zoning COBie.Zone Assessment COBie (Teicholz 2013) AEC 4 – Operation and Maintenance Information Assessment COBie (BIM Task Group 2012) AEC AHUs in the basement  Served spaces 342-8 Table 8: Compliance with BIM standards 4 CONCLUSION  In this paper, we present a novel division of typical IQ issues in BIM for FM into six categories. The information incompleteness and the value inaccuracy have been the subject of many research works, especially in connection with real objects (like assets). Nevertheless, there is still a great research demand for studying different accuracy aspects like value precision and correctness. As for spatial inaccuracy issues, whereas spaces as location of assets have been subject of several studies, there is a demand for future research about the relation between assets/MEP systems and served spaces, which is an essential aspect from FM perspective. System related issues are issues in the semantic of a model. To prevent such issues, researchers propose different instructions and checklist. Nevertheless, an automated method for identification and correction of such issues is a potential subject for future works. IQ issues related to the model incompatibility and uncoordinated information are well-studied fields by AEC researchers. Therefore, it is necessary that the owners deploy these studies to create suitable BIM-IQ strategies and assure the quality of required information for operation phase in the early phases of the project. This research shows the need for further studies on BIM quality and for automated IQ assessment approaches especially at the time of project handover to owners. References Akcamete, A., Akinci, B., and Garrett, J.H. 2010. Potential utilization of building information models for planning maintenance activities. Proceddings of the International Conference on Computing in Civil and Building Engineering. Short description Modeled information should meet the requirements in BIM standards  Example  Figure 8: BIM validation check for the architectural model of CIRS with Solibri # Used Term General Discussion Topic Assessment / Assurance Used Method Reference Domain 1 Compliance to Specific Standards Quality Management Assessment Vendor based Applications (Kasprzak et al.) AEC 2 Non-Compliant Elements Quality Control Assurance Using OPP (Messner and Kreirder 2013) AEC 3 Model Quality  BIM Performance Assessment Warnings (Du et al. 2014)  AEC 4 COBie Compliance  COBie standard worksheets Assurance COBie (USC 2012) AEC 5 BIM Quality  BIM requirements Assurance IFC (Kulusjärvi 2012) AEC 6 Model Control BIM Integration Assessment IFC Analysis (Manzione et al. 2011) AEC 7 Interoperability/IFC Support  Minimum BIM Assessment MVD (National Institute of Building Sciences 2007) AEC 8 Language Correctness Language Adequacy – – (Schuette and Rotthowe 1998) AEC 9 Compliance to the Model’s Metamodel Well-formedness – – (Mohagheghi and Aagedal 2007) CS 10 Typing Quality of raw data – – (Assaf and Senart 2012) CS 342-9 Asen, Y., Motamedi, A., and Hammad, A. 2012. BIM-Based Visual Analytics Approach for Facilities Management. Assaf, A. and Senart, A. 2012. Data Quality Principles in the Semantic Web. Semantic Computing (ICSC), 2012 IEEE Sixth International Conference on, IEEE, 226–229. Becerik-Gerber, B., Jazizadeh, F., Li, N., and Calis, G. 2011. Application areas and data requirements for BIM-enabled facilities management. Journal of construction engineering and management 138, 3, 431–442. Berard, O. 2012. A Framework for Assessing Design Information Quality from the Builder’s Perspective. In: BIM for Managing Design and Construction. Technical University of Denmark. BIM Task Group. 2012. COBie Data Drops. http://bit.ly/1bffidY  BSI. 2014. Specification for information management for the operational phase of assets using building information modelling. The British Standards Institution. Cervantes, M. 2012. 3 Levels of BIM Quality Assurance for Owners. PRACTICAL BIM 2012: Management, Implementation Coordination and Evaluation, University of Southern California. Cotts, D.G., Roper, K.O., and Payant, R.P. 2009. The Facility Management Handbook. AMACOM. Du, J., Liu, R., and Issa, R. 2014. BIM Cloud Score: Benchmarking BIM Performance. Journal of Construction Engineering and Management 140, 11, 04014054. East, E.W., Nisbet, N., and Liebich, T. 2013. Facility Management Handover Model View. Journal of Computing in Civil Engineering 27, 1, 61–67. GSA. 2011. GSA Building Information Modeling Guide Series: 08 - Guide for Facility Management.  Kasprzak, C., Ramesh, A., and Dubler, C. 2012 Developing Standards to Assess the Quality of BIM Criteria for Facilities Management. AEI 2013: Building Solutions for Architectural Engineering, ASCE, 680–690. Kulusjärvi, H. 2012. COBIM: Common BIM Requirements - Series 6 Quality assurance.  LACCD BIMS. 2010. LACCD Building Information Modeling Standards.  Lee, H.W., Oh, H., Kim, Y., and Choi, K. 2015. Quantitative analysis of warnings in building information modeling (BIM). Automation in Construction 51, 0, 23 – 31. Lee, Y.W., Strong, D.M., Kahn, B.K., and Wang, R.Y. 2002. AIMQ: A Methodology for Information Quality Assessment. Information & Management 40, 2, 133 – 146. Leite, F., Akinci, B., and Garrett, J. 2009. Identification of data items needed for automatic clash detection in MEP design coordination. 2009 Construction Research Congress, 416–425. Manzione, L., Wyse, M., Sacks, R., Van Berlo, L., and Melhado, S. 2011. Key Performance Indicators To Analyze And Improve Management of Information Flow In The BIM Design Process. CIB W78-W102 2011: International Conference, France. Messner, J. and Kreirder, R. 2013. Office of Physical Plant Case Study:  Methods used to analysis an owner organization for the planning of BIM implementation. Pennsylvania State University. Mohagheghi, P. and Aagedal, J. 2007. Evaluating Quality in Model-Driven Engineering. Modeling in Software Engineering, 2007. MISE ’07: ICSE Workshop 2007. International Workshop on, 6–6. National Institute of Building Sciences. 2007. Transforming the Building Supply Chain Through Open and Interoperable Information Exchanges.  Nepal, M.P., Staub-French, S., Pottinger, R., and Webster, A. 2012. Querying a building information model for construction-specific spatial information. Advanced Engineering Informatics 26, 4,904-923. Olson, J.E. 2002. Data Quality: The Accuracy Dimension. Morgan Kaufmann. OmniClass: A Strategy for Classifying the Built Environment. 2006. OmniClass.  SBCA. 2013. Singapore BIM Guide Version 2.  Schuette, R. and Rotthowe, T. 1998. The guidelines of modeling – an approach to enhance the quality in information models. In: Conceptual Modeling–ER’98. Springer, 240–254. Tang, P., Anil, E., Akinci, B., and Huber, D. 2011. Efficient and effective quality assessment of As-Is building information models and 3D laser-scanned data. Proceedings of ASCE International Workshop on Computing in Civil Engineering, Miami, FL, McGraw-Hill. Teicholz, P. 2013. BIM for Facility Managers. Wiley. Tilley, P.A., McFallan, S.L., and Tucker, S. 1999. Design and documentation quality and its impact on the construction process. Special Issue STEEL CONSTRUCTION. USC. 2012. Building Information Modeling (BIM) Guidelines. Wand, Y. and Wang, R.Y. 1996. Anchoring Data Quality Dimensions in Ontological Foundations. Communications of the ACM 39, 11, 86–95. 342-10  5th International/11th Construction Specialty Conference 5e International/11e Conférence spécialisée sur la construction    Vancouver, British Columbia June 8 to June 10, 2015 / 8 juin au 10 juin 2015   REVIEW OF BIM QUALITY ASSESSMENT APPROACHES FOR FACILITY MANAGEMENT Puyan A. Zadeh1, 3, Sheryl Staub-French1 and Rachel Pottinger2 1 Department of Civil Engineering, University of British Columbia, Canada 2 Department of Computer Science, University of British Columbia, Canada 3 p.zadeh@civil.ubc.ca  Abstract: Assessing the quality of information in building information models (BIM) at the time of project handover is critical for owners. Lack of quality information in delivered BIMs can cause significant issues in using BIM for facility management purposes, potentially limiting or preventing their use in building operations. Our studies of numerous BIM projects and deliverables have found that most BIMs created for design and construction today contain significant quality issues including inaccurate, incomplete, or unnecessary information. To make these models useful for building operations requires significant adjustment to the models, which can be very time-consuming and costly. This paper describes different types of quality issues identified through numerous case studies of BIM projects and categorizes them according to different model perspectives (entity, model, and user level) and relevant facility management perspectives (assets, MEP systems, and spaces). We identify the different characteristics of each type of quality issue and then systematically analyze relevant literature in the AEC and computer science domains to put these issues in context. This analysis highlights the ambiguity in characterizing information quality issues in a BIM and demonstrates the need for a comprehensive and consistent formalization of BIM quality. 1 INTRODUCTION Assessing the information quality (IQ) of building information models (BIM) for facility management (FM) purposes is a critical and challenging task for owners at the time of project handover. Lack of IQ in delivered BIM could have costly consequences for owners, including: manual adjustments to correct and complete the models; laser-scanning of (a part of) the building and related post processing efforts; and delays in the start of FM systems. Currently, researchers and owner organizations have different perspectives about the IQ of BIM, which consequently lead to different approaches to its assessment. Although organizations like U.S. General Services Administration (GSA) and British Standards Institution (BSI) have developed approaches to enforce BIM requirements throughout the project handover (BSI 2014, GSA 2011), such approaches are mainly based on generic checks and do not cover all required IQ characteristics for FM needs. For proper BIM-IQ assessment, it is necessary for owners to have a clear understanding about “what” are the potential quality issues, “which” IQ characteristics are relevant, and “how” to assess them. The objective of this paper is to contribute to the development of a comprehensive and consistent representation of BIM quality for owners. Through numerous case studies of BIM projects and interviews with FM personnel, we describe different types of quality issues and categorize them according to 342-1 different model perspectives (entity, model, and user level) and relevant facility management perspectives (assets, MEP systems, and spaces) in section 2. In section 3, we identify the different characteristics of each type of quality issue and then systematically analyze relevant literature in the AEC and computer science domains. This analysis highlights the ambiguity in characterizing information quality issues in a BIM, demonstrating the need for a comprehensive and consistent formalization of BIM quality for owners.  2 BIM QUALITY ANALYSIS FRAMEWORK FOR FM The motivation of this study has its roots in numerous case studies of BIM project deliverables and interviews with various FM personnel. In order to systematically analyze the different types of BIM quality issues, we developed an analysis framework considering different FM categories and model analysis perspectives (Table 1). Generally, FM information management systems (IMS) require information related to three essential terms: assets, MEP systems, i.e., mechanical, electrical, and plumbing/piping, as well as spaces. Although MEP systems may be considered a compilation of different assets, there are still differences between asset related and MEP system related IQ issues. Therefore, we divided the observed IQ issues accordingly in terms of assets, MEP systems, and spaces. Furthermore, the BIM-IQ issues can be categorized into different types from different analysis perspectives of model consumption. We determine these perspectives as: 1) entity level, which focuses on the smallest information pieces in a model; 2) model level, which considers the entire BIM as one information package; and 3) user level, which analyzes the information system from the model user’s perspective.  Table 1: BIM-IQ analysis framework for FM The analysis methodology below follows the structure of this framework. Specifically, we go through each issue type to analyze them systematically in correspondence with the related FM category. As the first step of the systematic analysis, we briefly describe each issue type by giving specific examples from a case study project. This description includes the IQ characteristics that are affected as well as their relevance for FM. In the next analysis step, we discuss the relevant literature for each type of quality issue. This includes the terms used by researchers to address these issues, the general topic that they discuss and their proposed approaches for preventing (IQ assurance) or identifying (IQ assessment) such issues. Finally, we evaluate these different perspectives and discuss the potential research gaps for each issue type. 3 TYPES OF QUALITY ISSUES AND RELEVANT LITERATURE This section presents a systematic analysis of each type of BIM quality issue from the BIM-IQ analysis framework introduced above in Table 1. In this analysis, we start with the entity level perspective and discuss the issue types related to assets, MEP systems, and spaces, and then continue with the model and user level perspectives.  BIM-IQ Perspectives FM Categories Entity Level Model Level User Level Asset Incomplete Assets  (Table 2) Inaccurate Values for Asset Attributes (Table 4) Inaccurate Asset Placement (Table 6) Compliance with BIM Standards (Table 8) Model Clashes Understand-ability of Information MEP Systems Incomplete MEP Systems (Table 3) Inaccurate Values for System Definitions (Figure 4) Inaccurate Spatial Allocation of MEP Systems (Table 7) Space Incomplete Spaces Inaccurate Values for Space Definitions (Table 5) Inaccurate Space Placement Issue Type Categories: Information Incompleteness (sec.  3.1) Value Inaccuracy (sec. 3.2 ) Spatial Inaccuracy (sec.  3.3) Model Incompatibility (sec.  3.4) Uncoordinated Information Incomprehens-ible Information 342-2 (2006). This list follows an object-oriented approach and so provides a hierarchy for each asset type that can have up to seven levels. The examples above and the similar references (GSA 2011, Kulusjärvi 2012, National Institute of Building Sciences 2007, SBCA 2013) show that the main focus of the AEC researchers regarding to the information completeness is on the IQ assurance by using one of the introduced methods above. However, significant issues remain in terms of how to deal with the incomplete models, how to incorporate such checklists and hierarchies and integrate them into the owner’s requirements and how to assess them in a given BIM. Incomplete MEP Systems: It is necessary for FM-IMS to define MEP systems completely in the mechanical BIM (GSA 2011, Kulusjärvi 2012, SBCA 2013, USC 2012). However, our analysis of BIM projects demonstrates that MEP systems are frequently defined inaccurately and incompletely in the mechanical BIM as in our case study (Table 3). This type of IQ issue is very similar to the incompleteness of assets with the difference that in this case one should investigate the entire components of a system or a sub-system. Table 3: Incompleteness of system definitions in BIM The information about systems is especially significant for intelligent troubleshooting processes where one does not exactly know which equipment is not working properly as well as for better understanding the consequences when an asset is broken. The completeness check for MEP systems should include the identification of assets without a specific system as well as systems that miss a major asset as a member (either the major asset is not modeled or it is not assigned to the system). As shown in Table 3, even though this IQ issue type and its consequences for the projects are not explicitly discussed in detail among AEC researchers yet, there are few (but important) references that propose IQ assurance approaches to avoid incompleteness in the MEP system definitions. Nevertheless, there is a research demand for evaluation of the assurance methods, and for the assessment of the required system attributes and the relevant system components (assets). Incomplete Spaces: In addition to assets and systems, spaces play also a crucial role in an FM-IMS. The representation of spaces in a BIM can support FM personnel particularly for what-if analyses, decision-making sessions, and routing the service components (Akcamete et al. 2010, Becerik-Gerber et al. 2011, Nepal et al. 2012). However, incomplete space information makes such processes more difficult. Researchers treat incompleteness of spaces in BIMs as an obvious issue that should be addressed. Therefore, this issue type has not been discussed as a separate topic yet and its assessment is usually included together with other building entities as a part of general checks, as in (Kulusjärvi 2012, LACCD BIMS 2010, National Institute of Building Sciences 2007, SBCA 2013, USC 2012).  Short description Identifying the missing MEP system components  Example  Figure 2: The piping system is incomplete for the mechanical room our case study # Used Term General Discussion Topic Assessment / Assurance Used Method Reference Domain 1 – Required BIM objects and properties Assurance Checklist (GSA 2011) AEC 2 – System BIM Assurance Checklist (Kulusjärvi 2012) AEC 3 – MEP Quality Assurance Assurance Checklist (SBCA 2013) AEC 4 – MEPF Specifications Assurance Checklist (USC 2012) AEC 5 – – Assurance COBie (BIM Task Group 2012) AEC (a) BIM (b) As-is 342-4 3.2 Value Inaccuracy (Entity Level) Inaccurate Values for Asset Attributes: In a desired BIM for FM, it is significant that the major assets are defined accurately. That means that the modeled assets must have the required attributes with precise values, their type must be correct and they need to be represented in the model with the correct size. In addition, the asset names must be clear, meaningful and not redundant. Inaccuracies in the attribute values is a very common IQ issue that we also recognized in our observations (Table 4).  Table 4: Inaccurate definition of modeled assets Reviewing related literature shows that when AEC researchers discuss the quality of BIMs, they strongly connect it to the accuracy aspect of the IQ and mainly use this term to address IQ characteristics related to the modeled “values”. However, much of the reviewed literature either does not specifically describe their interpretation of this term in more detail, as in (Du et al. 2014, GSA 2011, Kasprzak et al., National Institute of Building Sciences 2007), or the literature describes it in different ways. For example, (Berard 2012) refers to accuracy through different terms like information “precision”, “unambiguity” and “level of detail.” Du et al. (2014) define information accuracy as the degree to which the BIM models precisely reflect the physical real world conditions of a project. (Kulusjärvi 2012) address the accuracy aspect of IQ through the term “correctness.” These examples highlight a certain degree of ambiguity among AEC researchers when they discuss the quality values in a model. In contrast to the AEC researchers, the CS researchers organize these aspects in a different way. For example, (Lee et al. 2002) assign all value-related IQ aspects to the “intrinsic” IQ category. This category covers aspects like correctness, Short description Major assets must have the required attributes with precise values, their type must be correct and they need to be represented in the model at the right place with the correct size. Example  Figure 3: Example of inaccurate information for heat pump #03  # Used Term General Discussion Topic Assessment / Assurance Used Method Reference Domain 1 Accuracy Compliance and Submittals – – (GSA 2011) AEC 2 Accuracy Value of Information for Facilities Management Assessment – (Kasprzak et al.) AEC 3 Unambiguity and Level of Detail Precision Assessment Survey (Berard 2012) AEC 4 Accuracy Quality Assurance Assurance Checklist (SBCA 2013) AEC 5 Accuracy Data and Process Requirements Assurance Checklist (Becerik-Gerber et al. 2011) AEC 6 Accuracy Minimum BIM Assurance – (National Institute of Building Sciences 2007) AEC 7 Accuracy BIM Performance Assessment Quantity Takeoff (Du et al. 2014)  AEC 8 Correctness Quality Assurance Assurance – (Kulusjärvi 2012) AEC 9 Accuracy Quality of Raw Data – – (Assaf and Senart 2012) CS 10 Accuracy Data Quality – – (Olson 2002) CS 11 Accuracy and Precision Data Quality Dimensions – – (Wand and Wang 1996) CS 342-5 unambiguous, consistency, precision, reliability, etc. which match mostly with the different interpretations of accuracy in the AEC domain. Nevertheless, there is still a great potential for unambiguous analysis of each of these aspects. In addition, Table 4 shows that the researcher mainly focus on using checklist for accuracy assurance and assessment methods. However, using checklists is a very generic approach and leaves room for different interpretations.  Inaccurate Values for System Definitions: In contrast to the completeness of MEP systems, the accuracy of system definitions has not been discussed explicitly in the AEC literature yet. The main reason is that such systems can be considered as a composition of different assets (as system components) and so the value accuracy of asset’ attributes can result in a certain level of accuracy for the related system. Thus, the values of important system attributes can be calculated as summations of related asset attributes, as for system flow, total pressure, electricity voltage, medium type, etc. Therefore, most of the BIM authoring tools offer automated calculations for system attributes. Nevertheless, there are system attributes that describe specifically a system without a direct connection to the system components (Figure 5), like system names, types, classifications, and related documents (specs, sequence of operation, etc.). Thus, this IQ issue type has a high potential for further research to identify the consequences of inaccurate system information for FM-IMSs. Inaccurate Values for Space Definitions: Unlike incompleteness of spaces (and similar to other value inaccuracy issues discussed above), AEC researchers put emphasis on IQ of space definitions. Figure 5(a) in Table 5 shows an example from our case study where the space definition in BIM is inaccurate and incomplete. Figure 5(b) shows how building operation personnel keeps track of changes in the space arrangement with the help of printed PDF floor plans. The space related inaccuracies in the architectural BIM include spaces with incorrect utilization as well as spaces with different names from the actual space names in the building. A similar space related issue is the compliance of the room names with a required nomenclature by the owner. Such compliance is also documented in (Kulusjärvi 2012, LACCD BIMS 2010, National Institute of Building Sciences 2007, SBCA 2013, USC 2012).  Table 5: Inaccurate definition of modeled spaces in BIM Short description Identifying the inaccuracy in space definitions Example  (a) BIM (b) As-Is Figure 5: Inaccuracy and incompleteness in space definitions CIRS architectural BIM # Used Term General Discussion Topic Assessment / Assurance Used Method Reference Domain 1 – Spatial BIM Assurance Checklist (Kulusjärvi 2012) AEC 2 – Space Validation  Assurance COBie (USC 2012) AEC 3 Space Requirements Modelling Requirements Assurance Checklist (LACCD BIMS 2010) AEC 4 – Quality Assurance Assurance Checklist (SBCA 2013) AEC 5 Space Management Data Requirements for FM – – (Becerik-Gerber et al. 2011) AEC Figure 4: Inaccurately defined system attributes for an air terminal in our case study 342-6 3.3 Spatial Inaccuracy (Entity Level) This IQ issue category is about the inaccuracies in placing the entities in a three-dimensional environment as in BIM. This group of issue types is significant because the spatial placement of entities brings the architectural and mechanical information hierarchies together. Inaccurate Asset Placement: For facility operations, it is very important to find the related spaces for different assets (Asen et al. 2012). Becerik-Gerber et al. (2011) and Cotts et al. (2009) suggest facility managers ensure that the trade mechanics are familiar with equipment location. This highlights the significance of trades’ personal experiences with a facility where an intelligent FM-IMS is not available. Hence, using BIM could be a suitable alternative approach through accurate placements of assets in spaces. This requires both the accurate space definition as well as accurate asset placement in the space according to a spatial hierarchy. This placement is not only about identifying in which space is an asset located but also it is about determining where exactly this asset is placed in the assigned space. Table 6: Asset placement Finding assets’ exact location is challenging in projects without an as-built model, as in our case study. The reasons are first, mechanical and architectural models are usually separate models and need to be merged and adjusted, and second, it is challenging to assign assets correctly within a wall or ceiling to a space in an automated way. For instance, the height of a room begins from the top of the floor to bottom of the ceiling. Therefore, the challenge is to find the correct space for the assets within the floors’ slab. Figure 6 in Table 6 shows an example of assets within a second floor slab that belong either to the upper space (like diffusers) or to the space below (like light fixtures). Inaccuracy in asset placement in BIMs is a significant issue for creating FM-IMSs. Reviewing related literature shows that this IQ issue type is only marginally addressed in few publications and general expectation is that modelers assure the accuracy of asset-space relation by using a list of certain generic measures. However, a clear IQ assessment approach in this connection is missing. Inaccurate Spatial Allocation of MEP Systems: The relationship between MEP systems and spaces must include both the actual location of system components (assets) in the building as well as the served spaces by each MEP system. This is also emphasized in (Asen et al. 2012) where they describe such relationships as “spatial” for physical relation between assets/systems and spaces, and as “logical” for non-physically related assets/systems and spaces. The spatial relationship between MEP systems and spaces can be considered as a summation of space assignments for individual system components (assets). Thus, through an accurate system definition and correct placement of assets in spaces, this kind of issues can be avoided. The logical relation corresponds to the identification of which space(s) are served through a system (Table 7). This is significant for systems with a central role in a building, which usually serve spaces (mechanical zones) other than the location of their major assets. Short description Identifying the location of assets in BIM, i.e., the suitable space and the correct position in the space Example  Figure 6: Assets within the floor slab of CIRS, including pipes, radiant heaters and light fixtures # Used Term General Discussion Topic Assessment / Assurance Used Method Reference Domain 1 Spatial relationship Visual Analytics for FM – – (Asen et al. 2012) AEC 2 – Quality Assurance Assurance Checklist (SBCA 2013) AEC 3 Spatial BIM BIM Requirements Assurance Checklist (Kulusjärvi 2012) AEC 342-7 Table 7: Spatial allocation of MEP systems Identification of served spaces is very relevant for FM (East et al. 2013, GSA 2011, Teicholz 2013, USC 2012), since such significant systems usually require frequent maintenance and the buildings operators need to know which building parts are affected when a system needs to be maintained. Automated identification of served spaces for MEP systems is more complicated than the location finding challenge above. Our review of related literature in Table 7 reveals that in the discussion about spatial allocation of MEP systems, researchers have been focused so far on the quality assessment measures for BIM mainly using COBie spreadsheets. 3.4 Model Incompatibility (Model Level) Model incompatibility is about the model compliance with BIM standards and is an important IQ issue type from the model level perspective (Table 8). This issue type is about whether or not the information within the model is compatible with specific data structures. In other words, this issue type corresponds to the way the information is organized in BIM and it is related to all FM categories (assets, MEP systems and spaces). This is an important IQ characteristic, since the compliance with a standardized data structure, such as IFC, can shape the modeling process, facilitate information exchange between different BIM authoring tools and as a result can increase the quality of collaboration in a project (Kulusjärvi 2012, LACCD BIMS 2010). In addition to IFC standards, some literature propose the use of BIM exchange standards (like COBie) as alternative benchmarks for model compatibility assessments. For instance, the authors in (East et al. 2013, Kasprzak et al., Teicholz 2013, USC 2012) suggest to perform compatibility checks with COBie standard worksheets as a quality control approach. Moreover, the authors in (USC 2012) propose the compatibility checks with EcoDomus as an alternative to COBie for IQ control purposes. Our literature review results that AEC researchers have comprehensively researched model compatibility with BIM standards (Table 8). However, they address it through very different terms. For example, the authors in (Kasprzak et al.) describe it as “Data & Process Standardization” and propose that the modeled information should be in compliance with specific standards, like the internal standards of the Office of Physical Plant (OPP) at the Pennsylvania State University. This approach is similar to the “Quality Control” checks that the authors in (Messner and Kreirder 2013) demand as a part of owner requirements. (Schuette and Rotthowe 1998) address the validation of an information system as the “Language Adequacy” of the model. This emphasizes the importance of this IQ aspect, i.e., the information structure as the “grammar” for organizing data, for the researchers before the BIM era. An alternative approach to check the validation of model data structure is to analyze the warnings that specific BIM artifacts report as described in (Du et al. 2014, USC 2012). An extensive analysis about the warning messages in BIM artefacts is given in (Lee et al. 2015). They divide these warnings into three categories: annotation, information and geometry warnings. The interesting point about such researches is that they do not only propose approaches for assessing IQ issues but also provide analyses to identify the reason of those warnings, which makes this type of researches more valuable. Short description Identifying the spaces that are served by MEP system  Examples  Figure 7: Air Handling Units (AHUs) that are located in the basement serve different spaces in the building # Used Term General Discussion Topic Assessment / Assurance Used Method Reference Domain 1 Served zones FM Handover Model Assessment COBie (East et al. 2013) AEC 2 Served area BIm for FM – – (GSA 2011) AEC 3 Zoning COBie.Zone Assessment COBie (Teicholz 2013) AEC 4 – Operation and Maintenance Information Assessment COBie (BIM Task Group 2012) AEC AHUs in the basement  Served spaces 342-8 Table 8: Compliance with BIM standards 4 CONCLUSION  In this paper, we present a novel division of typical IQ issues in BIM for FM into six categories. The information incompleteness and the value inaccuracy have been the subject of many research works, especially in connection with real objects (like assets). Nevertheless, there is still a great research demand for studying different accuracy aspects like value precision and correctness. As for spatial inaccuracy issues, whereas spaces as location of assets have been subject of several studies, there is a demand for future research about the relation between assets/MEP systems and served spaces, which is an essential aspect from FM perspective. System related issues are issues in the semantic of a model. To prevent such issues, researchers propose different instructions and checklist. Nevertheless, an automated method for identification and correction of such issues is a potential subject for future works. IQ issues related to the model incompatibility and uncoordinated information are well-studied fields by AEC researchers. Therefore, it is necessary that the owners deploy these studies to create suitable BIM-IQ strategies and assure the quality of required information for operation phase in the early phases of the project. This research shows the need for further studies on BIM quality and for automated IQ assessment approaches especially at the time of project handover to owners. References Akcamete, A., Akinci, B., and Garrett, J.H. 2010. Potential utilization of building information models for planning maintenance activities. Proceddings of the International Conference on Computing in Civil and Building Engineering. Short description Modeled information should meet the requirements in BIM standards  Example  Figure 8: BIM validation check for the architectural model of CIRS with Solibri # Used Term General Discussion Topic Assessment / Assurance Used Method Reference Domain 1 Compliance to Specific Standards Quality Management Assessment Vendor based Applications (Kasprzak et al.) AEC 2 Non-Compliant Elements Quality Control Assurance Using OPP (Messner and Kreirder 2013) AEC 3 Model Quality  BIM Performance Assessment Warnings (Du et al. 2014)  AEC 4 COBie Compliance  COBie standard worksheets Assurance COBie (USC 2012) AEC 5 BIM Quality  BIM requirements Assurance IFC (Kulusjärvi 2012) AEC 6 Model Control BIM Integration Assessment IFC Analysis (Manzione et al. 2011) AEC 7 Interoperability/IFC Support  Minimum BIM Assessment MVD (National Institute of Building Sciences 2007) AEC 8 Language Correctness Language Adequacy – – (Schuette and Rotthowe 1998) AEC 9 Compliance to the Model’s Metamodel Well-formedness – – (Mohagheghi and Aagedal 2007) CS 10 Typing Quality of raw data – – (Assaf and Senart 2012) CS 342-9 Asen, Y., Motamedi, A., and Hammad, A. 2012. BIM-Based Visual Analytics Approach for Facilities Management. Assaf, A. and Senart, A. 2012. Data Quality Principles in the Semantic Web. Semantic Computing (ICSC), 2012 IEEE Sixth International Conference on, IEEE, 226–229. Becerik-Gerber, B., Jazizadeh, F., Li, N., and Calis, G. 2011. Application areas and data requirements for BIM-enabled facilities management. Journal of construction engineering and management 138, 3, 431–442. Berard, O. 2012. A Framework for Assessing Design Information Quality from the Builder’s Perspective. In: BIM for Managing Design and Construction. Technical University of Denmark. BIM Task Group. 2012. COBie Data Drops. http://bit.ly/1bffidY  BSI. 2014. Specification for information management for the operational phase of assets using building information modelling. The British Standards Institution. Cervantes, M. 2012. 3 Levels of BIM Quality Assurance for Owners. PRACTICAL BIM 2012: Management, Implementation Coordination and Evaluation, University of Southern California. Cotts, D.G., Roper, K.O., and Payant, R.P. 2009. The Facility Management Handbook. AMACOM. 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Tilley, P.A., McFallan, S.L., and Tucker, S. 1999. Design and documentation quality and its impact on the construction process. Special Issue STEEL CONSTRUCTION. USC. 2012. Building Information Modeling (BIM) Guidelines. Wand, Y. and Wang, R.Y. 1996. Anchoring Data Quality Dimensions in Ontological Foundations. Communications of the ACM 39, 11, 86–95. 342-10  REVIEW OF BIM QUALITY ASSESSMENT APPROACHESFOR FACILITY MANAGEMENTPuyan A. Zadeh*Sheryl Staub-FrenchRachel PottingerJune 10, 2015?ICSC2015BIM for FMCreating intelligent FM systems out of BIMProject handover is essential in information lifecycleDeliverables (incl. BIM) must include required information pieces for FMAssessing the information quality (IQ) of BIM from FM perspectiveMotivationIQA  |  ICSC2015  |  Puyan A. Zadeh, Dr.-Ing.  |  UBC Civil Engineering  |  June 10, 2015  |  2Motivation case study: The Centre for Interactive Research on Sustainability (CIRS)Creating FM information system based on delivered BIM  IQ issuesChallenges: “What” are the typical IQ issues? “Which” IQ characteristics are relevant?  “How” to assess these BIM-IQ characteristics?Motivation©Google EarthCIRSIQA  |  ICSC2015  |  Puyan A. Zadeh, Dr.-Ing.  |  UBC Civil Engineering  |  June 10, 2015  |  3 Categorization of IQ issues Determining FM and BIM perspectives Creating an analysis framework Identification of BIM-IQ characteristics Analysis of related literature and assessment approachesApproachIQA  |  ICSC2015  |  Puyan A. Zadeh, Dr.-Ing.  |  UBC Civil Engineering  |  June 10, 2015  |  4 Interviews, observations and literature review Analysis of O&M workflow Three key terms for creating intelligent FM information systems: Assets MEP systems Spaces  BIM perspectives: Entity level Model level User levelDetermining FM and BIM perspectivesIQA  |  ICSC2015  |  Puyan A. Zadeh, Dr.-Ing.  |  UBC Civil Engineering  |  June 10, 2015  |  5BIM-IQ Analysis Framework for FMBIM-IQ PerspectivesFM Cat. Entity Level Model Level User LevelAsset Incomplete Assets Inaccurate Values for Asset AttributesInaccurate Asset PlacementCompliance with BIM StandardsModel ClashesUnderstandability of InformationMEP SystemsIncomplete MEP SystemsInaccurate Values for System DefinitionsInaccurate Spatial Allocation of MEP SystemsSpace Incomplete Spaces Inaccurate Values for Space DefinitionsInaccurate Space PlacementIssue Type Categories:Information Incompleteness Value InaccuracySpatial InaccuracyModel IncompatibilityUncoordinated InformationIncomprehensible InformationIQA  |  ICSC2015  |  Puyan A. Zadeh, Dr.-Ing.  |  UBC Civil Engineering  |  June 10, 2015  |  6Existence of “necessary” information2 types of benchmarkChallenges: 1.What should be checked? Assets with central roles in system Assets which need frequent maintenance Assets that can be remotely monitored and controlled2.How to assess?Information IncompletenessIQA  |  ICSC2015  |  Puyan A. Zadeh, Dr.-Ing.  |  UBC Civil Engineering  |  June 10, 2015  |  7Information IncompletenessHow to assess?IQA  |  ICSC2015  |  Puyan A. Zadeh, Dr.-Ing.  |  UBC Civil Engineering  |  June 10, 2015  |  8Existence of entities / objectsVisual checkWalkthroughs  Laser-Scanning  Information takeoff Querying the model Export: COBie, etc.Information Incompleteness?BIMas-builtIQA  |  ICSC2015  |  Puyan A. Zadeh, Dr.-Ing.  |  UBC Civil Engineering  |  June 10, 2015  |  9Is every asset assigned to an MEP system?Information Incompleteness of MEP Systems0 5000 10000 15000 20000 25000 30000NORDSTROMPharmacyRAMCIRSAssigned Assets to an MEP SystemAssigned Assets Total Assets6.91%83.37%98.61%93.65%IQA  |  ICSC2015  |  Puyan A. Zadeh, Dr.-Ing.  |  UBC Civil Engineering  |  June 10, 2015  |  10Information Incompleteness of MEP SystemsAnalysis of the system assignments in the Pharmacy building IQA  |  ICSC2015  |  Puyan A. Zadeh, Dr.-Ing.  |  UBC Civil Engineering  |  June 10, 2015  |  11Inaccurate Values for AttributesIQA  |  ICSC2015  |  Puyan A. Zadeh, Dr.-Ing.  |  UBC Civil Engineering  |  June 10, 2015  |  12Inaccurate Values for AttributesIQA  |  ICSC2015  |  Puyan A. Zadeh, Dr.-Ing.  |  UBC Civil Engineering  |  June 10, 2015  |  13Inaccurate Values for AttributesPage 27Challenge: • Organization of documents (7125 pages, 374 PDFs, 14 folders for CIRS)• Unsearchable documents• Asset by asset check is required• Many specs are part of the name or typeIQA  |  ICSC2015  |  Puyan A. Zadeh, Dr.-Ing.  |  UBC Civil Engineering  |  June 10, 2015  |  14Entity level: IncompletenessValue InaccuracySpatial InaccuracyCategorization of BIM-IQ Issues for FM?IQA  |  ICSC2015  |  Puyan A. Zadeh, Dr.-Ing.  |  UBC Civil Engineering  |  June 10, 2015  |  15Model level:Standards’ IncompatibilityUncoordinated Model InconsistencyUser level Incomprehensibility  InaccessibilityCategorization of BIM-IQ Issues for FM?IQA  |  ICSC2015  |  Puyan A. Zadeh, Dr.-Ing.  |  UBC Civil Engineering  |  June 10, 2015  |  16Categorization of IQ issues FM key terms and BIM perspectives Identification of BIM-IQ characteristicsAEC lit. address these issues: Very generic More quality “assurance” than quality “assessment” Issues related to the model semantic have a great research potential Ambiguity in issue identification Concrete assessment approaches are missingConclusionIQA  |  ICSC2015  |  Puyan A. Zadeh, Dr.-Ing.  |  UBC Civil Engineering  |  June 10, 2015  |  17Puyan A. Zadeh, Dr.-Ing. Email: p.zadeh@civil.ubc.caWeb: http://puyanx.comTel.: 604 499 8937June 10, 2015REVIEW OF BIM QUALITY ASSESSMENT APPROACHESFOR FACILITY MANAGEMENTExistence of attributesUsing predefined listsFor example for an asset: Name location Category / System Manufacturer  Model Serial numberInformation IncompletenessIQA  |  ICSC2015  |  Puyan A. Zadeh, Dr.-Ing.  |  UBC Civil Engineering  |  June 10, 2015  |  19Correctness of entity attributes valuesMainly accuracy “assurance” through ChecklistsOne by one entity checkingi.e. filtering the entity in model and compare it to benchmarkInformation AccuracySource: Version 1.0 27.03.2012 - Parties to the © COBIM projectIQA  |  ICSC2015  |  Puyan A. Zadeh, Dr.-Ing.  |  UBC Civil Engineering  |  June 10, 2015  |  20Where is an asset?Inaccurate Asset PlacementSpatial Inaccuracy: Asset- Space IssuesIQA  |  ICSC2015  |  Puyan A. Zadeh, Dr.-Ing.  |  UBC Civil Engineering  |  June 10, 2015  |  21Challenges:No direct asset-space connectionDucts and pipes are usually separate systems Identification of systems that connect the asset and served spaceServed Spaces by an Asset or a SystemIQA  |  ICSC2015  |  Puyan A. Zadeh, Dr.-Ing.  |  UBC Civil Engineering  |  June 10, 2015  |  22Categorization of BIM-IQ Issues for FM Incompleteness Value Inaccuracy Spatial Inaccuracy??IQA  |  ICSC2015  |  Puyan A. Zadeh, Dr.-Ing.  |  UBC Civil Engineering  |  June 10, 2015  |  23Categorization of BIM-IQ Issues for FM Standards’ Incompatibility Uncoordinated Model Inconsistency?IQA  |  ICSC2015  |  Puyan A. Zadeh, Dr.-Ing.  |  UBC Civil Engineering  |  June 10, 2015  |  24Categorization of BIM-IQ Issues for FM Incomprehensibility  Inaccessibility© retrosection.comIQA  |  ICSC2015  |  Puyan A. Zadeh, Dr.-Ing.  |  UBC Civil Engineering  |  June 10, 2015  |  25Categorization of BIM-IQ Issues for FM Incomprehensibility  Inaccessibility Standards’ Incompatibility Uncoordinated Model Inconsistency Incompleteness Value Inaccuracy Spatial InaccuracyIQA  |  ICSC2015  |  Puyan A. Zadeh, Dr.-Ing.  |  UBC Civil Engineering  |  June 10, 2015  |  26Many specs are part of the name or typeInaccurate Values for Asset AttributesIQA  |  ICSC2015  |  Puyan A. Zadeh, Dr.-Ing.  |  UBC Civil Engineering  |  June 10, 2015  |  27

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