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Building Information Modeling (BIM) for existing buildings — Literature review and future needs [Autom. Constr. 38 (March 2014) 109–127]


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While BIM processes are established for new buildings, the majority of existing buildings is not maintained, refurbished or deconstructed with BIM yet. Promising benefits of efficient resource management motivate research to overcome uncertainties of building condition and deficient documentation prevalent in existing buildings. Due to rapid developments in BIM research, involved stakeholders demand a state-of-the-art overview of BIM implementation and research in existing buildings. This paper presents a review of over 180 recent publications on the topic. Results show scarce BIM implementation in existing buildings yet, due to challenges of (1) high modeling/conversion effort from captured building data into semantic BIM objects, (2) updating of information in BIM and (3) handling of uncertain data, objects and relations in BIM occurring in existing buildings. Despite fast developments and spreading standards, challenging research opportunities arise from process automation and BIM adaption to existing buildings' requirements.
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Building Information Modeling (BIM) for existing buildings literature review
and future needs
Authors: Rebekka VOLKa,b, Julian STENGELa, Frank SCHULTMANNa
a Institute for Industrial Production (IIP), Karlsruhe Institute of Technology (KIT), Hertzstraße 16,
76131 Karlsruhe, Germany,,,
b corresponding author (+49 721 608 44699)
Please cite the article as:
Volk, R.; Stengel, J.; Schultmann, F. (2014): Building Information Models (BIM) for existing buildings
literature review and future needs - Automation in Construction 38, pp.109-127, DOI:
While BIM processes are established for new buildings, the majority of existing buildings is not
maintained, refurbished or deconstructed with BIM yet. Promising benefits of efficient resource
management motivate research to overcome uncertainties of building condition and deficient
documentation prevalent in existing buildings.
Due to rapid developments in BIM research, involved stakeholders demand a state-of-the-art overview
of BIM implementation and research in existing buildings. This paper presents a review of over recent
180 publications on the topic. Results show scare BIM implementation in existing buildings yet, due to
challenges of (1) high modeling/conversion effort from captured building data into semantic BIM
objects, (2) updating of information in BIM and (3) handling of uncertain data, objects and relations in
BIM occurring in existing buildings.
Despite fast developments and spreading standards, challenging research opportunities arise from
process automation and BIM adaption to existing buildings’ requirements.
Keywords As-built BIM (Building Information Modeling)², Existing buildings, Facility management
, Maintenance
, Retrofits
, Deconstruction¹, Dismantling¹, Demolition¹, , ‘Scan-to-BIM’, Reverse
Paper type - Review paper
1 Introduction
Resource scarcity, sustainability challenges and stricter decrees for recycling and resource efficiency
in buildings [1] motivate the Architecture, Engineering, Construction, Facility Management (FM) and
communities to manage resources efficiently [2]. Due to long building life cycles,
maintenance and deconstruction management are likewise major levers to cope with resource
efficiency and to enable closed-loop material cycles. Especially in industrialized countries with low new
construction rates, activities of the construction sector increasingly shift to building modifications,
retrofits and deconstruction of existing buildings [3,4].
In the past decades, there had been a growing interest of the construction sector in using Building
Information Models (BIM)
due to many benefits and resource savings during design, planning, and
construction of new buildings [59]. Development of 3D modeling started in the 1970s, based on the
In this paper we use the term ‘deconstruction’ for the denomination of the last building LC stage with further
subcategories. Other sources like ISO 22263:2008 or OmniClass Table 32:2012 refer to this stage synonymously
as ‘demolition’, ‘decommissioning’, ‘disassembling’, ‘dismantling’, ‘recycling’ or ‘end-of-life’. Besides, we use
the term 'maintenance' for the LC stage of building service life with synonyms like 'operations and
maintenance', 'facility management', 'retrofit' or 'refurbishment'.
Synonyms: Building Construction Information Model, Building Information Modeling
early computer-aided design (CAD) efforts in several industries. While many industries developed
integrated analysis tools and object-based parametric modeling (being the basic concept of BIM), the
construction sector confined for quite some time to the traditional 2D design [7,8]. BIM modeling was
introduced in pilot projects in the early 2000s [3] to support building design of architects and
engineers. Consequently, major research trends focused on the improvement of preplanning and
design, clash detection, visualization, quantification, costing and data management [7,10]. Lately,
specialized tools of design, architecture and engineering professions join the basic functionalities,
such as energy analysis, structural analysis, scheduling, progress tracking or jobsite safety [11]. The
use of BIM concentrates on preplanning, design, construction and integrated project delivery of
buildings and infrastructure, but since recently, research focus shifts from earlier life cycle (LC) stages
to maintenance, refurbishment, deconstruction and end-of-life considerations [2,7,1115] especially of
complex structures.
Buildings and structures differ in types of use (e.g. residential, commercial, municipal, infrastructural),
in age (e.g. new
, existing
, heritage) and in ownership (e.g. private owner, housing association,
authorities, universities). These differing framework conditions are influencing the application of BIM,
its level of detail (LoD) and its supporting functionalities regarding design, construction, maintenance
and deconstruction processes due to stakeholders’ requirements.
According to recent surveys, BIM is suitable for larger and more complex buildings and applied by the
respondents of recent surveys in commercial, residential, educational, healthcare and many other
building types [15,16]. But as less than 10% of the respondents are facility managers, owners or
deconstructors, these trends do not necessarily reflect current use of BIM in existing buildings [15,16].
Although BIM implementation requires profound process changes of the involved parties, the benefits
in new construction projects both of private and institutional owners are manifold and often confirmed
by involved stakeholders [7,8,17,18]. Major benefits consist in design consistency and visualization,
cost estimations, clash detection, implementation of lean construction or improved stakeholder
collaboration. Major challenges in new buildings refer to change from design-bid-build processes to
integrated project delivery (IPD) and to the increased time effort and knowledge required for BIM use.
BIM implementation in existing buildings however faces other potentials and challenges. Potential
benefits of using BIM in FM seem to be significant [11,19,20], e.g. as valuable ‘as-built’ (heritage)
documentation [7], maintenance of warranty and service information [11,19,21], quality control [95,96],
assessment and monitoring [7,11,19], energy and space management [11,22], emergency
management [19] or retrofit planning [4,19]. Decontamination or deconstruction processes could also
benefit from structured up-to-date building information to reduce errors and financial risk, e.g. through
deconstruction scheduling and sequencing, cost calculation, rubble management, optimization of
deconstruction progress tracking or data management.
Several types of information are necessary to manage a facility or to perform retrofit measures in
buildings [11]. Apart from contact and general building information, detailed data on installed
components and equipment is needed such as service zones, installation dates, installation type,
vendor/manufacturer, geometries and exact location, materials and compositions, physical properties,
warranties, as well as maintenance history since completion [11,12]. When building LC draws to a
close, further information on occupancy history, actual and detailed (hazardous) material information,
components’ masses and connections, recycling or disposal options, potential recycling qualities, load
bearing structures or deconstruction techniques with associated time and costs per component [2,24]
is relevant for deconstruction planning. During a building LC, numerous responsible stakeholders and
subcontractors are involved and often withdraw their specialized information e.g. on components’
installation [7].
As Building Information Model (BIM) is a tool to manage accurate building information over the whole
LC [25], it is adequate to support data of maintenance and deconstruction processes [2,7,24]. As BIM
initially was intended to support design and construction processes, some information such as
In this paper, we refer to new buildings as planned buildings, buildings under construction or recently completed
In this paper, we refer to existing buildings as already but not recently completed buildings.
loadbearing structures is already documented in preexisting BIM while others like LCA information
might be added or updated for a required functionality. Since the introduction of international COBie
standard, stakeholders are able to store maintenance information in BIM in a structured way and thus
in a valuable form of facility documentation [7].
In many existing buildings, incomplete, obsolete or fragmented building information is predominating
[11,23]. Missing or obsolete building information might result in ineffective project management,
uncertain process results and time loss or cost increases in maintenance, retrofit or remediation
processes. As existing buildings often lack as-built documentation due to omitted updating, limitations
of BIM use in existing buildings and research challenges are expected.
This paper aims (1) at a comprehensive literature review of BIM creation, implementation and
research in existing buildings and (2) at the identification and discussion of current trends and
research gaps in this area. The scope includes the specific needs and potentials of BIM for existing
residential and non-residential buildings of several ownerships. But it rather disregards considerations
on infrastructures and heritage structures, due to their different maintenance requirements and (if
necessary) deconstruction processes. The results of this research are useful for industry
professionals, BIM developers and researchers involved in the implementation of BIM in existing
buildings and structures.
The following section 2 defines BIM in a narrow and a broader sense to assure common
understanding of the terminology. Besides, two major BIM creation processes are described. In
section 3, examined literature sources and the applied review method is presented. Section 4 focuses
on the state-of-the-art BIM creation, implementation and research approaches in existing buildings
with regard to functionality, level of detail (LoD), informational, technical and organizational structures
in maintenance and deconstruction. Section 5 discusses identified results and research gaps and
section 6 concludes our findings.
2 Definition of Building Information Model (BIM)
Building (Construction) Information Model (BIM) is defined by international standards as shared digital
representation of physical and functional characteristics of any built object […] which forms a reliable
basis for decisions [26]. BIMs originate from product models [27,28] that are widely applied in the
petrochemical, automotive or shipbuilding industry [7,29]. BIM represents real buildings virtually over
the whole LC as semantically enriched, consistent, digital building models [7,30,31]. BIM is realized
with object-oriented software and consists of parametric objects representing building components
[12,27,32]. Objects may have geometric or non-geometric attributes with functional, semantic or
topologic information [7,29]. For example, functional attributes can be installation durations or costs,
semantic information store e.g. connectivity, aggregation, containment or intersection information and
topologic attributes provide e.g. information about objects’ locations, adjacency, coplanarity or
BIM can be seen from a narrow and a broader perspective (Figure 1). BIM in a narrow sense (‘little
bim’ [33], ‘tool’ [7]) comprises solely the digital building model itself in the sense of a central
information management hub or repository [7,30,34,35] and its model creation issues (technical
issues see section 4.3) [27]. Commercial BIM platforms offer integrated data management,
component libraries and general functionalities [7]. Widespread differentiations of BIM are 3D (spatial
model with quantity takeoff), 4D (plus construction scheduling) and 5D (plus cost calculation) BIM
[7,27]. Further BIM inherent functionalities of dominating vendors are extensively discussed in
literature [7,36] and section 4.1.
Different BIM creation processes for new³ and existing4 buildings are depicted in Figure 2. For new
buildings, BIM is created in a process over several LC stages, starting from inception, brief, design to
production (case I) and part of the project delivery. As BIM sometimes is not used by all AEC/FM
stakeholders in the building LC yet, some create isolated BIM solely for a designated, single purpose.
In existing buildings - depending on the availability of preexisting BIM - BIM can be either updated
(case II) [37] or created anew (case III). In Europe, more than 80% of residential buildings are built
before 1990 [38] and mainly do not have a building documentation in BIM format [19,3941].
Therefore if implemented in practice, costly and mainly manual reverse engineering processes
(‘points-to-BIM’, ‘scan-to-BIM’) (case III) help recapturing building information [42,43].
As depicted in Figure 1, BIM in a broader sense (‘BIG BIM[33,44]) can be divided into interrelated
functional, informational, technical and organizational/legal issues. Depending onto the stakeholders
needs and the project requirements, a BIM model is used to support and perform expert services for
buildings such as energy or environmental analyses [7]. Therefore, two types of expert software might
interact with a BIM model: (1) data input applications providing services of import, data capture and
monitoring, data processing or transformation of captured data into BIM or (2) data output applications
providing reports or technical analyses such as structural and energy analyses or clash detections
(see also Table 3).
Figure 1: Relations between LC stage as well as functional, informational, technical and organizational
issues of BIM, partly according to [8,17]
In this paper, we refer to BIM functionalities (functional issues, see section 4.1) as services or
capabilities that are provided by BIM in the narrow sense or its accompanying data output software.
This data output or functionality depends on stakeholder and building or project requirements as well
as on the buildings’ LC stage. On the other hand, functionalities determine informational or
organizational issues e.g. with respect to data exchanges or communication processes. This
relationship becomes evident within the following example: if e.g. an energy analysis of a building is
required, specific information is needed (e.g. U-values of components, radiation level or orientation of
the building) to perform the analysis. If this information is not inherent in the narrow BIM model, a
structured data exchange between BIM model and expert functionality has to take place.
Organizational and legal structures (roles) determine the access to and define responsibilities for input
and analysis data and their correctness.
Depending on the required functionality, a suitable informational structure and data exchange
(informational issues, see section 4.2) with the model is necessary to guarantee interoperability
between different software systems without information loss. Functional and informational
requirements again determine model characteristics (technical issues, see section 4.3) through LoD,
required model capacities and consequently required model creation processes. Organizational and
legal issues (see section 4.4) determine the stakeholder roles, their information rights and liabilities,
their model access (read, write) or their obligation to provide a special functionality or data output.
Figure 2: BIM model creation processes in new or existing buildings depending on available, preexisting
BIM and LC stages with their related requirements [45,46]
3 Review approach
3.1 Originality
In literature, numerous reviews of BIM implementation and research approaches in new buildings
[7,8,17,27,29,47,48] predominate, while BIM usage in existing buildings is rather neglected yet [11,19].
Existing reviews either cover one or two aspects separately or concentrate on few cross-sectional
challenges. Functional issues in the areas of maintenance [7,11,12,14,20,45,4956] and
deconstruction [2,24] are addressed separately and mainly for new buildings (see Table 3). Also,
informational [26,27,50,5760], technical [19,31,40,43,45,6166] and organizational/legal [21,67]
issues of BIM use are often examined separately. Publications on informational issues mainly consider
new buildings’ requirements, whereas the publications on technical issues focus either on capturing
construction data or geometries of existing buildings for processing into digital building models
[19,31,62]. Papers with regard to organizational/legal issues concentrate on collaboration of consortia
partners in new building projects and in facility management (FM).
Publications with a broader scope considering more than one of the previous issues [6,68,69] (e.g.
LoD in BIM) and covering several BIM issues [7,8,17,27] mainly for new buildings are sporadic.
Publications explicitly devoted to BIM for existing buildings, especially without preexisting BIM and
discussing related research challenges, are rare [19].
Questionnaires on BIM implementation status and benefits are quite constantly conducted [8,11,15
17,47,48]. But surveys do not focus on post-construction stakeholders, processes and related issues
yet. Less than 10% of the respondents are owners, facility managers or deconstructors, while the
majority originates from the disciplines of architecture, cost calculation, construction or project
management [1517]. Thus, these surveys do not provide representative statements on usage,
hindrances and major trends of BIM in existing buildings.
As to our knowledge there is no comprehensive overview of recent research of BIM for existing
buildings, we partly try to close this gap with the contribution at hand. The objective of this paper is to
examine BIM in a broader sense, as depicted in Figure 1, and to analyze the required BIM functionality
in existing buildings as well as the influential dependencies between informational, technical and
organizational issues of BIM. Also, specific or multidisciplinary research gaps are identified and
3.2 Methodology
To review BIM for existing buildings comprehensively, our three-step approach examines both
academic and applied publications [17].
In a first step, journals in academic and applied databases
are identified that contribute to BIM
implementation or LC stage-dependent BIM functionalities in existing buildings. The found journals
either focus on (1) built environments and its processes (AEC/FM) partly integrating sustainability
issues, (2) information technology application in the construction sector, (3) remote sensing
technologies, surveying and computer vision or (4) LC considerations and rubble management (see
Table 1).
Table 1: Examined Journals, classified according to their scope
Journals (Publisher)
Archives of Civil and Mechanical Engineering (ELSEVIER)
Structure & Infrastructure Engineering: Maintenance, Management, Life-Cycle Design & Performance (T&F)
Advanced Engineering Informatics (ELSEVIER)
Multidiscipline Modeling in Materials and Structures (EMERALD)
International Journal of Computer Vision (SPRINGER)
The Photogrammetric Record (WILEY)
LC & waste
International Journal of Life Cycle Assessment (SPRINGER)
Waste management (ELSEVIER)
In order to limit this broad scope in a second step to LC stages of maintenance and deconstruction, we
perform a keyword search in the aforementioned academic journals as well as in databases and
conference proceedings. Main keywords are ‘BIM’, ‘building (information) model’, ‘existing buildings’,
‘maintenance’, ‘facility management’, ‘retrofit’ and ‘deconstruction’1. With this standard practice in
academic literature review we receive a comprehensive picture of recently published research and
implementation efforts. Besides, to consider actual developments beyond academic publications we
reviewed applied publications of relevant stakeholders such as professional associations (e.g. ASCE
Journal databases:,,,,,,, and others;
Conference proceedings: 3D(IM)PVT, CIB, CRC, ICCCBE (ASCE), ISARC, ISPRS, SASBE, SB and other
conferences on data processing, computer vision or building modeling.
and their journals), of standard committees (e.g. buildingSMART, openBIM), of software solution
providers (e.g. ASI) and of state authorities. Within the found publications, we further differentiated
between publications mentioning or not mentioning ‘BIM’ in keywords or abstract (see Figure 3 and
Figure 4).
Due to the applied method, the review excludes research currently underway that is not available in
mentioned databases, or studies which have not been published in English yet.
3.3 Data analysis
Over 180 publications (books and academic/applied papers) and relevant standards and internet
sources were reviewed, thereof 90 journal papers, 63 conference papers and 26 other publications
(e.g. books or papers in applied journals). As Figure 3 shows, over 80 of the reviewed publications are
explicitly devoted to BIM (‘BIM’ in abstract or key words). The remaining publications nevertheless are
relevant: some either (1) do not mention BIM in its keywords or abstract, although addressed in the
publication, or (2) regard 3D building models that are not explicitly BIM, partly due to unclear definition,
e.g. models that lack semantic information or parametric representation of components (such as
surface, BREP, CSG or CAD models), or (3) deal with related topics, such as cloud computing or
semantic web services. It also becomes clear from Figure 3, that most BIM papers were published
after 2008 with a considerable intensification in the latest years.
Figure 3: Frequency of reviewed publications per year of publication
Figure 4 presents different topics (see also Table 2) associated with BIM in existing buildings in
relation to their year of publication. Several recent trends become obvious:
The trend of BIM publications continues unabated and the range of published topics increases
Topics of research areas like data management, documentation, controlling and progress tracking
or measurement are published with almost constantly raising tendency.
Demolition/Deconstruction planning in the context of BIM is a novel area of research.
Figure 4: Number of reviewed publications with designated BIM topics per year (multiple naming
possible), depicted with moving average on 3 periods
Table 2 displays the frequency of major LC stages, topics and spatial foci in the reviewed journal and
conference papers. In total, most publications deal with BIM creation and modeling and respectively
with existing buildingsexteriors. Fewer papers deal with maintenance aspects of data management
and “as-built” documentation, quality assessment/deviation analyses and survey/measurements
accuracy on building component level. Only few research approaches discuss deconstruction
functionalities in BIM in conference proceedings of ASCE 2012 and ICCCBE 2012 [2,24]. A third paper
in this area focuses on rubble management through RFID [70]. Related to the total amount of reviewed
papers, on average each paper covers 1.7 areas of contribution. Spatial foci of the reviewed papers
are mainly on the buildings’ exterior or interior, followed by building components.
4 Implementation and research approaches of BIM in existing buildings
In this section, BIM in a broader sense is described with its functional, informational, technical and
organizational/legal issues in building maintenance and deconstruction. Apart from depicting state-of-
the-art implementation, we present current research approaches and identify future areas of research.
4.1 Functional issues
4.1.1 Functionalities and applications
Due to numerous design, engineering, construction, maintenance and deconstruction services during
building LC, potential applications and required functionalities of BIM in buildings and infrastructures
are manifold. Depending on the stakeholders’ and project requirements, BIM with e.g. architectural,
constructional, piping and electrical, structural, fabricational or monitoring functionality is needed.
Functionalities are either inherent in 3D, 4D or 5D BIM (e.g. quantity takeoff, scheduling or cost
calculation) or they are attached to BIM as independent expert applications. Expert functionalities use
the underlying BIM data to support, extend, calculate or simulate specific business requirements (e.g.
perform structural analyses). Results are either reintegrated into BIM or reported separately.
Functionalities are based on process maps, which describe the logical flow of information and
activities as well as the stakeholders roles within a particular functionality [26].
Table 2: Frequency of different LC stages and topics in 184 reviewed publications (multiple naming
Number of reviewed
Publications focusing on
building LC stages of …
Design (incl. inception and brief)
Construction (incl. planning, scheduling)
Maintenance (incl. retrofits, monitoring)
Deconstruction (incl. planning, execution)
Others (e.g. prefabrication)
Average of LC stages per paper
Publications with
contributions in…
BIM creation and modeling
Data management
Documentation (‘as-built’)
Survey/Measurement accuracy
Quality assessment, deviation analyses
Object recognition
Monitoring or progress tracking
Augmented/Virtual reality
Demolition/Deconstruction management
Average of topics per paper
Publications with spatial
focus on…
Building exterior (e.g. facades, roof)
Building interior (e.g. rooms)
Building components
Building supporting structure (e.g. walls, slabs)
Others (e.g. street views, city models)
Average of spatial foci per paper
Table 3: Examples for major applied or developing BIM functionalities for existing buildings
Clash detection, Spatial program validation, BIM quality assessment
Construction progress tracking
Cost calculation or Cash flow modeling (5D)**
Daylight simulation
Deconstruction, Rubble management
Deviation analysis, Quality control, Defect detection
Documentation, Data management and Visualization
Energy/Thermal analysis and control, Carbon foot printing
Localization of building components, Indoor navigation
Life cycle assessment (LCA), Sustainability
Monitoring, Performance measurement (through sensors)
Operations and Maintenance (O&M), Facility management (FM)
Quantity takeoff (3D)
Retrofit/Refurbishment/Renovation planning and execution
Risk scenario planning
Safety, Jobsite safety, Emergency Management
Scheduling (4D)
Space Management
Structural analysis
Subcontractor and supplier integration, Prefabrication (e.g. of steel,
precast components, fenestration, glass fabrication [7])
* available in every major BIM software [7] ** often country-specific
Table 3 displays major examples of inherent and expert functionalities applied in practice and
examined in research. Currently, research rather focuses on expert functionalities for new buildings,
such as energy and carbon reduction analyses, construction progress tracking (matching of captured
data with preexisting BIM), deviation analyses (quality control, defect detection) and jobsite safety.
According to BIM’s original application in new construction, applied functionalities concentrate on
design and visualization, procurement, manufacturing, construction management and coordination
rather than on commissioning, facility management or deconstruction. But recently, planning and
handover processes shift from design-bid-built to integrated project delivery (IPD) in a collaborative
atmosphere [15], considering the value of “as-built” BIM information for FM, retrofit and deconstruction
As new construction rates in industrialized countries stagnate, planning and implementing
refurbishment and retrofit measures in existing buildings gain in importance [3]. Various digital tools for
building capture and auditing are available, such as 2D/3D geometrical drawings, tachometry, laser
scanning or automatic locating of images, but need increased modeling and planning efforts of skillful
personnel [3,35,130]. Existing maintenance functionalities - so called Computerized Maintenance
Management Systems (CMMS) or Computer Aided Facility Management (CAFM) - focus on (web-
based) data management, maintenance schedules and equipment warranties of increasingly complex
buildings [23,99], but they are intensely developed [11,150] e.g. with respect to deterioration and
cause-effect relationships [99]. Partly, FM systems include laser scanning of existing facilities and
bidirectional information flow between Geographic Information Systems (GIS) and maintenance data
[124,127]. While there are many research efforts in FM and BIM related topics, an industry-wide
implementation is lacking yet [11]. But case studies show reasonable results e.g. in Sydney Opera
House [13], campus buildings [4,20] and other facilities [7].
Most of the mentioned FM, refurbishment and deconstruction research approaches require an
available BIM of a recently constructed building [3]. If a BIM of the designated structure exists, the
functionalities and processes of planning and performing conversions, refurbishments and
deconstructions might be performed with smaller adjustments. But if only an outdated or no BIM is
available, processes start with building auditing, documentation review and analyses of previous and
current building properties [3,130] to provide a profound basis for planning and cost estimating. This
area is intensely researched [31,62,130,151153] and focus of section 4.3.
Although digital costs estimation, quantity take-off, data management and reporting tools are used in
deconstruction industry, BIM functionalities of deconstruction [2,24], vulnerability and collapse
analyses [146,154], emergency management [141], localization or documentation of hazardous or
contaminant materials [2,30] or risk scenario planning [17] are rare in literature yet. Besides, other
potential BIM functionalities are not covered yet like deconstruction execution planning and progress
tracking, recycling and rubble management, secondary component and raw material auctions,
recycling network logistics, monitoring of hazardous components or automated reporting to authorities.
One reason might be the low participation of facility managers, retrofitters and deconstructors in the
development of BIM functionalities [15]. Another reason might result from COBie and OmniClass
standards, that define several properties and attributes to support maintenance processes
[53,124,155], but only partly enable deconstruction and recycling functionalities (e.g. with demolition
date, recycled date, ease of relocation or removal, material properties). The analysis of OmniClass
properties (Table 49: Pre Consensus Approved Draft from 2012-10-30) showed, that many properties
defined for manufacturers and their processes could easily be adapted to deconstructors requirements
e.g. deconstruction lead and idle times, deconstruction and shipping costs, deconstruction and
recycling methods or source limitations for deconstructors (see also Table 4). But deviations, damages
or deterioration effects are not depicted yet and need further research [99,130].
Table 4: Literature and own suggestions of IFC attribute extensions to describe inaccuracies,
uncertainties or future processes and treatments occurring in existing buildings
Potential IFC attribute extensions
(main category)
Existing building
audits and
Uncertain/lacking information in
captured data
Clutter, measurement errors
Vegetation and site conditions
Trees, shrubbery etc.
Ground conditions like sloping ground
Uncertain/lacking information on BIM
Damages, defects or deterioration of building elements
Deviations in geometric or topological object information like
uneven floors/walls or non-orthogonality;
Concealed and thus assumed components and components’
physical properties like detailed layers, structure or
(hazardous/contaminant) material composition
Uncertain/lacking information on
BIM relations
(Non-)loadbearing structures, containing relation, adhering
relation etc.
Location properties
Locations of sorting, recycling/reprocessing and disposal
facilities, temporal storage facilities
Properties of time and money
Deconstruction lead and idle times
Deinstallation/dismantling costs
Object treatment costs e.g. for reinforcement, repair,
decontamination, reprocessing, recycling, disposal
Shipping costs to recycling/disposal facilities or other
construction sites
Source properties
Source limitations for deconstructors and decontaminators like
required operating and storage spaces
Methods of deconstruction or recycling
Equipments with their characteristic durations, costs,
resources (personal, machines)
Dependencies and precedences in maintenance and
deconstruction processes
Deconstructors’ certifications
Consultant and authorities’ properties, e.g. information
Product properties
Disassembly types and groups
Possible future or performed object treatments e.g.
reinforcement, repair, decontamination, reprocessing,
recycling, disposal options
Structural behavior during deconstruction
Properties of sustainability, e.g. recycling material quality,
recycling and disposal rates of building components,
hazardous materials
Process planning
Safety plans and prevention measures or deconstruction
progress tracking
Possible future emissions
Noise, dust or vibration emissions from deconstruction
processes or other emissions according to LCA information
with related prevention measures and costs
As described functionalities require accurate information on objects, relations and attributes in BIM,
maintenance and updating of information in BIM remains a major challenge and area of research
[11,21]. Due to long lifetimes of buildings and infrastructure, recent research also adresses BIM model
evolutions, continuous model maintenance and management of temporal data [12] as well as the
interoperability with developing BIM and expert software [11,37] (see also section 4.2).
4.1.2 Accuracy and capability
BIM functionalities require a certain accuracy, information richness and actuality of the underlying data
to fulfill their purposes [6,7]. A frequently mentioned concept to describe information richness of BIM
objects is Level of Detail’ or also referred to as ‘Level of Development’ (LoD). LoD defines geometric
and non-geometric attribute information provided by a model component [157,158], often referenced
to a point of time, LC stage or to a contractual responsibility. To enable e.g. analysis or scheduling
functionalities, the required LoD of objects attributes and relations has to be defined, such as
durations, dependencies or precedence information. Some LoD in literature are depicted in Table 5,
whose definitions differ in geometric accuracy, quality or completeness of semantic information
Table 5: Levels of Detail / Levels of Development (LoD) in BIM models according to literature
Levels of
Approximate geometry, Precise geometry, Fabrication level/construction documentation
Conceptual, Approximate geometry, Precise geometry, Fabrication, As-built
As-designed/As-planned, As-built, As-used
Schematic design, Detailed design, Level of fabrication (shop model)
Levels of
LOD 100, LOD 200, LOD 300, LOD 400, LOD 500
In new construction projects, LoD increases in the course of LC stages from inception to
production/construction depending on the changing requirements and refinements from draft to
realization. In literature, functionality-related LoDs are defined for general modeling [31], 3D imaging
[161] and energy performance [162]. In existing buildings, required functionality determines the LoD
and the resulting cost and effort associated with BIM creation [6]. For maintenance functionalities, the
Construction Operations Building information exchange (COBie) standard defines a LoD for technical
equipment, regarding type and location, make, model and serial numbers, tag, installation date,
warranty and scheduled maintenance requirements [155] (see also section 4.2.2). Klein et al. [43]
define 2% geometric deviation for maintenance applications but do not provide a LoD of non-
geometric information. For deconstruction functionalities (incl. rubble management) no adequate LoD
is defined yet.
Beyond LoD, several BIM assessment frameworks are under development, such as CMM
, CMMI, P-
CMM, Object/Element Matrix or ISO/IEC 15504 (SPICE) [155,159,160]. As ISO/IEC 15504 generally
formulates the process assessment, the Capability Maturity Model (CMM) is used in BIM contexts to
evaluate if BIM projects or processes reach the desired level of functionality [163]. CMM assessment
framework formulates minimum capabilities and requirements of BIM model and process maturity
[163] with ten levels of BIM maturity defined for categories of: Spatial Capability, Roles/Disciplines,
Data Richness, Delivery Method, Change Management or Maturity Assessment, Business Process,
Information Accuracy, Lifecycle Views, Graphical Information, Timeliness and Response as well as
Interoperability and Industry Foundation Class Support.
Professional associations try to define and harmonize related concepts and ratings measuring BIM’s
data requirements and capabilities, but yet there has not emerged a standard assessment framework
of BIM for both new and existing buildings [160,163].
4.2 Informational issues and interoperability
Expert functionalities are linked with a BIM model through Information Delivery Manual (IDM)
frameworks and Model View Definitions (MDV) providing relevant information, facilitating data
exchange and avoiding ambiguities [59]. As shown in Figure 5, IDM frameworks and MVD specify
storage, conversion and information exchange in BIM and thus form the link between functional,
technical and organizational issues. The exchange requirement model (ERM) describes the
information flows with regard to: the requesting users in their roles, the relevant information for a
designated process, the moment of the information flow, the content and the receiving user/role. Non-
The Capacity Maturity Model defines a minimum of information in BIM according to the following
categories: Spatial Capability, Roles or Disciplines, Data Richness, Delivery Method, Change
Management or ITIL Maturity Assessment, Business Process, Information Accuracy, Lifecycle Views,
Graphical Information, Timeliness and Response, Interoperability and Industry Foundation Class
Support [163]
proprietary standards like Industry Foundation Classes (IFC) (ISO/PAS 16739) [165] and International
Framework for Dictionaries (IFD) (ISO 12006-3) [183] enhance data exchange between different BIM
systems on object level minimizing information loss. Also, initiatives like UniClass and OmniClass
further structure and unify the information content of organizational roles, project phases, services or
component properties. The following sections depict the related informational issues in more detail.
Figure 5: Information Delivery Manual (IDM) framework (ISO 29481-1:2010) [26] and its relations to
functional, technical and organizational issues in BIM
4.2.1 Information Delivery Manual (IDM) framework
The IDM framework defines the functionality-related exchange of process information in BIM through
process maps, interaction maps and the associated Exchange Requirement Model (ERM) [166].
Process maps describe the flow of activities within a particular topic, the actors’ roles and information
required, created and consumed, while interaction maps define roles and transactions for a specific
purpose or functionality [26]. The ERM is the technical solution defining a “set of information that
needs to be exchanged to support a particular business requirement” [26] or functionality and is
interrelated with MVD [26]. In literature, an IDM framework for energy analysis is presented in [167].
But for maintenance or deconstruction processes IDM frameworks are not defined yet [166].
4.2.2 Model View Definition (MVD)
A Model View Definition (MVD) or IFC View Definition defines a subset of the IFC […] that is needed
to satisfy one or many Exchange Requirements of the AEC industry [58]. A MVD structures relevant
information for efficient information flow between stakeholders in building-related processes or for e.g.
energy or structural analyses. MVD definition depends on the required functionality and the referred
BIM objects and attributes in process and interaction maps [59,168].
For maintenance purposes, COBie is the predominant, vendor-neutral, international standard MVD to
exchange contact and general facility information as well as information about spaces, floors, zones,
components, technical systems and equipment [51,57,58,169,170]. Newly, this standard is
complemented by a responsibility matrix that allots the kinds of required data to the responsible
persons or roles [171]. As COBie contains general building information, spaces/zones, and information
on equipments such as their geometries, locations, certificates and warranties, performance data and
testing results, preventive maintenance, safety and emergency plans or start-up/shut-down
instructions [11,172], it can be seen as a core model accompanied and extended by domain-specific
exchange requirements. E.g. the extension of WSie is planned to provide performance information
about piping connections, flow rates or other controlling information [173]. MVD for other domain-
specific functionalities are depicted in Table 6. As many MVD refer to new buildings’ requirements, the
listed MVD are only partly relevant and adequate in maintenance processes, due to differing
requirements and information structures. Besides, so far there is no publication defining MVD for
audits of existing buildings [130] (e.g. with respect to structural and inventory survey) or MVD for
deconstruction, recycling or rubble management processes and functionalities in BIM yet.
Table 6: Exemplary Model View Definitions (MVD) for BIM functionalities in IFC2x3 format; others can be
found in [168]
Model View Definitions (MVD)
BIM Service interface exchange, (web services and server-client communication)
Building Automation Modeling information exchange (control and building automation systems)
Electrical System information exchange (delivery of electrical power within facilities)
Equipment Layout information exchange
IFC2x3 Coordination View Version 2.0 (optional with Quantity Takeoff, Space boundary or 2D
Annotation add-on view)
IFC2x3 Structural Analysis View (released)
HVAC (Heating, Ventilation, Air-conditioning, Cooling) information exchange
Life-Cycle information exchange, with the refinement of Building Programming information exchange
LCie, BPie
FM Basic Handover with Construction-Operations Building information exchange
Quantity Takeoff information exchange
Spatial validation
Water System information exchange
4.2.3 Industry Foundation Classes (IFC)
Data exchanges are possible either directly, or through proprietary or non-proprietary exchange
formats [7]. IFC defined in ISO/PAS 16739:2005 [165] is the dominant non-proprietary exchange
format of building information between AEC/FM software [7,27,67,179]. It was developed to represent
building information over the whole buildings’ LC (except deconstruction) [7,180] and to facilitate data
transfer between BIM modeling software (e.g. Autodesk or Bentley), IFC viewers (e.g. IFCStoreyView)
and expert software applications (e.g. ‘Model Checker’ from Solibri). Data exchanges between source
and receiving software systems are performed through mainly proprietary translators with own data
structures [7]. Certifications like ‘openBIM’ of buildingSMART and NBIMS award software solutions
with high IFC interoperability.
Interoperability of BIM in different LC stages and functionalities still is limited [27,48] due to
incomplete, differently or ambiguously used IFC attributes, denotations or contents [30,34,59,181] (see
section 4.1.1). Often, one-way interfaces from BIM model to expert applications are used [7]. Recent
developments focus on the implementation of Specifiers' Properties
Information Exchange (SPie) and
semantic web technologies in open formats and ontologies like HTML, XHTML, bcXML, gbXML, e-
COGNOS, COBie, IFCXML, IFC, ifcOWL or CIS/2 to enable expert software applications
[7,60,179,182]. But most applications restrict to academic use yet [179].
4.2.4 International Framework for Dictionaries (IFD) Library respective
buildingSMART Data Dictionary (bSDD)
The International Framework for Dictionaries (IFD), defined in ISO 12006-3 [183,184] and recently
renamed in buildingSMART Data Dictionary (bSDD), is a terminology standard for BIM libraries and
ontologies [185]. It is an object-oriented database of multi-lingual terms which define concepts used in
the construction industry [181] and respective IFC characteristics, such as denotations of objects,
parts, attributes, units or values. Regional adaptations and customization of IFC are possible due to
globally unique ID (GUID) tags defined of an international working group [181]. IFD supports
interoperability of BIM content through GUID between BIM and project or product specific data
Standards ISO 12006 parts 2 and 3 structure BIM content, while OmniClass™ specifies BIM content
according to AEC requirements into construction results, construction resources and construction
processes [186]. A profound analysis of OmniClass properties revealed that some properties for
representing existing buildings and related processes are lacking yet (see Table 4 in section 4.1.1).
BIM objects’ properties and attributes are used synonymously.
Future challenges remain the assignment of attributes to LC stages [185187], to MVD and to process
interfaces [7].
4.3 Technical issues
As BIM in a narrow sense is modeled to fulfill required functionalities [153,188] for example in
maintenance or deconstruction, technical issues depend on the LoD required by the designated
functionality. Therefore when applied to existing buildings, the functionality-related LoD determines the
technical specifications of data capture, processing and BIM model creation. The BIM creation process
can be differentiated between for new and for existing buildings due to varying building information
quality, information availability and functionality requirements (see Figure 2). For new buildings, model
creation of the “as-planned” BIM is done in an interactive, iterative process with commercial design or
planning software (Figure 6 left part) and allows updating to an “as-built” BIM (case I). Since many
existing buildings have rather insufficient, preexisting building documentation either preexisting BIM is
updated (case II) [37] or a “points-to-BIM” process is performed (case III) [4,43,62,68] to gather and
model actual building conditions (Figure 6 right part). To create an as-built BIM from scratch
(case III), geometrical and topological information of building elements has to be gathered, modeled
and complemented by semantic property/attribute information manually. If a reliable data capture
technique could provide an as-built BIM at reasonable time and cost [19,42,62,65,152,153], existing
buildings could benefit from BIM usage e.g. regarding documentation, visualization or facility
The three cases differ considerably in potential modeling effort. In most existing buildings, insufficient
building information and no available preexisting BIM lead to application of case III which is discussed
in further detail below.
Figure 6: BIM creation processes for new and existing buildings, partly from Huber et al. [62]
4.3.1 Data capture
If building information is insufficient for required functionalities, techniques of data capture
or survey
are applied [35]. The required LoD determines all following steps from technique selection to model
creation due to its great influence on required data quality, data volume and processing effort.
Synonyms: data capture, data acquisition, data retrieval. However, building survey implies
measurements from building components.
Figure 7 shows non-contact techniques further differentiated into image-based, range-based,
combined or other techniques; contact methods consist of manual or other techniques [39,189,190].
Image- and range-based techniques extract mainly spatial, color and reflectivity information. In
practice, semi-automated laser scanning with total stations is prevalent [153], although affected with
disadvantages such as high equipment cost and fragility as well as difficulties in scanning reflective,
transparent and dark surfaces [43,61]. Besides, this technique needs further extensive data
processing and modeling steps (see following sections) on conventional computers and current
approaches have rather minor LoDs [4,30,31,52,66,130,151,191,192].
Manual techniques capture mostly spatial and other component-related information. Few approaches
focus on other techniques like tagging [110,111,193] or utilize preexisting building information
[25,130,194] to gather additional information such as components’ dimensions, materials, textures,
functions, connections, positions or maintenance periods. RFID or barcode tags are rather installed in
new buildings [7,70,195], because in existing buildings tagging is limited by installation effort (e.g. to
retrofits), readability range and interoperability [110,111,193].
Table 7 summarizes the major data capturing techniques of laser scanning, photogrammetry and
tagging that are relevant in research [19,31,40,43,61,77,151,196] and decisive features for technique
selection. Main characteristics are cost, time, LoD and environmental conditions during data capture
(e.g. light, weather, vegetation, concealments, clutter). Combinations of techniques are common and
try to overcome drawbacks of individual capturing techniques [25,63,83,190,197199]. In practice,
laser scanning is widely applied to measure infrastructures’ and buildings’ dimensions [79,94,200], and
to record and update city surfaces [201].
Figure 7: Systematic overview of data capturing and surveying techniques to gather existing buildings’
information [7,19,45,61,78,189,202]
Maintenance functionalities require a high LoD of components, the installed equipment, services and
appliances [50]. Therefore, tagging is rather inadequate for application in maintenance in terms of
spatial accuracy, LoD and degree of automation. Time and cost restrictions are major decisive
features [2] in deconstruction processes, but a related LoD and appropriate capturing technique is yet
to be defined.
Recent research focused on capturing mainly geometric rather than semantic representations of
buildings and feeding point cloud data into BIM software [4,19,43,152,199,203210]. But new
developments intensely research process models for automated BIM modeling from captured data
(‘scan-to-BIM’) and improvements in LoD [31,151,192] to enhance application in existing buildings. In
order to perform a comprehensive audit on existing buildings, the mentioned data capturing
techniques might be combined with other methods of non-destructive testing to analyze materials and
properties. Possible methods could include material- or texture-based recognition [151] and structure
recognition beyond surface through ground penetrating radars, radiography, magnetic particle
inspection, sonars or electro-magnetic waves [205] or tags installed during retrofits.
Table 7: Characteristics of main data capturing techniques in the construction sector
Decisive features
Data capturing techniques
Applicability in existing buildings
Spatial accuracy, Level of Detail (LoD)
Influence of size and complexity of the
Influence of environmental conditions
Importability into BIM
Data volumes
Degree of automation
Equipment portability
Equipment durability and robustness
4.3.2 Data processing
As functionality requirements determine the required LoD and thus the data capturing technique,
functionality influences data volume, processing and related time and effort. Data processing is
performed to enable the recognition of functionality-relevant BIM objects in previously captured
building data, e.g. to detect installations or fittings for maintenance purposes.
During processing steps, image-based and range-based point cloud data is registered, aligned and
merged into the same coordinate system [31]. This is mostly done interactively, either through defined
coordinates or detected characteristics such as descriptors or tie points [31,61]. Then, data is cleaned
from noise, irrelevant information and clutter [31,203] and often decimated to improve computing time.
Data captured with other techniques is processed according to its data format, the required
functionality and the object recognition method [25,70,110,130,194].
Applied to fulfill maintenance or deconstruction functionality requirements of complex structures, data
processing might overrun reasonable computing times due to increased LoD, high data volumes or
limited computing capacity of mobile devices. Further developments in computing performance of
mobile devices and research in outsourcing of computing processes on cloud servers might enable
faster data processing.
4.3.3 Object recognition
The captured and processed building data is used to recognize building components and their
characteristics relevant to required functionalities. The recognition of objects includes object
identification, extraction of relational and semantic information as well as treatment of concealments
and remaining clutter [31]. Methods and tools of object recognition differ due to geometric complexity
of the building, required LoD, and applied capturing technique, data format, or processing time.
Figure 8: Systematic review of object recognition approaches applied in existing buildings
Figure 8 shows data-driven, model-driven and other recognition approaches. Data-driven approaches
extract building information from captured and processed data and can be differentiated into feature-,
shape-, material-based and statistical matching methods. Model-driven approaches are rather based
on a predefined structure such as e.g. topologic relations or constraints and perform matching of
captured data through knowledge or contextual information. Other approaches include manual
identification or tags. Some publications combine data- and model-driven approaches to overcome
drawbacks of individual methods [62,64,65,196]. Coarse and mainly planar building components such
as walls, ceilings, floors, doors, windows and clutter are recognized in small scenes of single or few
rooms [62,64,65] with recognition rates between 89 and 93%. But nevertheless, research approaches
try to further improve LoD and recognition rates as well as handling data uncertainty through statistical
(thresholds), contextual (semantic nets, relations) or interactive (machine learning) methods
In order to enable maintenance functionalities, detailed information e.g. on technical equipment
(HVAC/MEP) [50] such as the course of ducts, installation dates, material layers or composites is
necessary. This information is not automatically recognized in buildings by current approaches yet, but
requires intense user input and interaction [40]. However, other industries might provide promising
approaches [31,214]. Deconstruction-related LoD in recent research focus on structural components
[2,24] yet, that might be recognized in image- or range-based data. But sophisticated functionalities
e.g. with regard to components’ connections, hazardous components, components’ layers or recycling
qualities demand a higher LoD that would require high analytical testing efforts and user inputs.
4.3.4 Modeling
denotes the creation of BIM objects that represent building components, including both
geometric and non-geometric attributes and relationships. If BIM is modeled on the basis of previously
captured building information, the preceding data capture, processing and recognition methods
influences data quality through the deployed technique and the provided LoD. To compare different
approaches and their modeling capacities, created models might be assessed e.g. with respect to
modeling or recognition accuracy, LoD or CMM6 [31,163]. Yet, no standard BIM assessment method
has been established to compare model qualities (see section 4.1.2).
In this context, modeling does not refer to simulations or optimizations of processes or parameters
(e.g. time or cost). Such calculations might be performed e.g. in expert functionalities on BIM data.
In practice, “as-built” BIM modeling is done interactively in a time-consuming and error-prone process
[7,19,31,189], e.g. with BIM modeling software of the few major vendors Autodesk Revit and
Navisworks, Bentley Architecture, Graphisoft ArchiCAD, Tekla or Nemetschek Allplan. Specialized
software in the area of reverse engineering, data capture, processing and BIM modeling is analyzed in
Table 8. Although some allow the rapid generation of building floor plans [130,215] or offer BIM
integration, the depicted software solutions are far from automated or semi-automated BIM modeling
of existing buildings.
In research, automated BIM modeling or transformations of surface models into volumetric,
semantically rich entities are in its infancy [19,151]. Many reviewed publications cope with (semi-)
automated modeling of building surfaces or components with respect to their geometrical
representations. However, they do not regard component properties or semantic information yet
[19,43,152,199,203210,216]. If non-geometric attributes like functional, relational, economical or
semantic information of existing buildings are integrated into BIM, it is done interactively or semi-
automated [130,151153]. E.g. concealed building components like ducts, pipes, conduits or plumbing
(HVAC/MEP) can only be modeled with high user input yet [40]. Due to an effortful BIM creation
process, model creation of existing buildings either focuses on coarse building components or is not
applied yet. Besides, the high LoD, e.g. required for specific maintenance or deconstruction
considerations is not compatible with current time and cost restrictions in the AEC/FM/D sector.
Furthermore, our review reveals that object attributes and relations relevant for maintenance and
deconstruction functionalities are not widespread modeled yet, partly due to undefined properties (see
Table 4), unavailable object libraries containing older building components or unspecified LoD.
As skilled personnel and high efforts are necessary to model BIM of existing buildings, further
research in automated capturing, processing and modeling could reduce building auditing cost and
increase productivity in BIM-based maintenance and deconstruction processes.
Table 8: Technology analysis of commercial capturing, processing and modeling software with respect to
the BIM or CAD integration
Data capturing techniques
Australis [217,218]
Export of DFX and ASCII
Architectural application,
DWG file export
Canoma [221]
Surface texturing of CAD
INOVx RealityLinx
Model [222]
Plant application
NuBAU freac
Interactive creation of
Export in DXF, textured
surfaces and elevation
Polyworks Modeler
Import of IGES/STEP files,
no architectural application
Geomagic Design X
(Rapidform XOR2)
Parametric modeling, no
architectural application
RiSCANPro [215,227]
Automated creation of
Vela Systems Field
BIM [228,229]
Integrated in Autodesk
X: Used technique
*: Digital photos
4.4 Organizational and legal issues
The use of BIM and the integrated product delivery (IPD) concept in new construction requires
profound process changes [7]. As this also applies when BIM is used in maintenance and
deconstruction processes, organizational issues are discussed in this section that influence the
implementation of BIM in existing buildings such as collaboration of stakeholders, contractual
relationships or liability.
4.4.1 Collaboration of stakeholders
Throughout the construction industry, collaboration and data exchange still is mainly document-based
[48,150]. Traditionally, resistances or lack of education/training resulted in a rather inefficient
collaboration [9,11,36,67,230]. Depending on the project, collaboration through BIM over the whole
building LC can improve data and process management in a central information repository [30,67] and
facilitate role and responsibility management through attached groupware or web services [21].
In new buildings, collaboration through BIM is increasing, especially due to improving capacities of
communication media [150], such as e.g. groupware [101,102], BIM server and cloud computing
[34,100,120,231,232], mobile devices [34,76,120,231233] and augmented reality approaches
[76,233]. But also the spreading of collaboration standards (e.g. Dutch VISI-Standard) and amplified
training of personnel helps to overcome the implementation problems and isolated use of BIM
[21,67,234,235]. Besides, requests of building owners and political pressure in some countries like UK
or USA increasingly foster BIM collaboration in new construction [44,236239].
Available BIM collaboration systems focus on functionalities of content management, viewing and
reporting rather than on model creation or system administration yet, but they are further developing
[150]. Nevertheless, literature still indicates prevalent social and institutional obstacles inhibiting BIM
implementation in the construction sector. Often mentioned obstacles are a fragmented Architecture,
Engineering, Construction, Facility Management and Deconstruction (AEC/FM/D) industry [48],
resistance to changes in employment patterns and processes [48,150,240], slowly adapting training of
personnel, lacking customized collaboration systems [150], as well as prevailing problems of liability,
data security and interoperability [7,17,21,30,48,66,241].
For maintenance and deconstruction purposes in existing buildings, stakeholders and their roles are
defined in COBie and can be linked with BIM objects for which they are responsible [50,130]. Since
the majority of existing buildings are not maintained or deconstructed with BIM yet, stakeholders'
collaboration might remain ineffective. Many available and partly BIM-integrated FM software solutions
as well as IPD will enhance FM functionalities and collaboration. But regarding deconstruction,
activities and functionality-specific process or interaction maps of BIM are not developed or
implemented yet. Due to dominant time and cost restrictions in deconstruction, research focus rather
on time and cost optimizations rather than on digitally supported collaboration (through BIM).
4.4.2 Responsibility, liability and model ownership
As depicted previously, collaboration systems have four major domains: content management, model
content creation, viewing/reporting and system administration [150]. Especially the second domain
raises most discussed topics of standard of care, contractual protection of model ownership and
intellectual property, as well as of authorized uses and sensitive information in integrated project
delivery (IPD) [17,48,158,239,242,243]. Insurance matters like shifting or sharing of risk as well as
allocation or compensation of responsibility are also important issues [242244].
For BIM use in new buildings, the American Institute of Architects (AIA), the Associated General
Contractors of America (AGC) and ConsensusDocs are working on respective contractual guidelines
[7] and are publishing contract samples [7,44,158,245]. But legal uncertainties in BIM implementation
and in fee specifications in AEC/FM/D sectors [11] of other countries often remain.
As many processes in FM and deconstruction are not based on BIM yet, respective contracts have not
yet been developed and standardized for these applications. Although e.g. responsibilities for
hazardous materials onsite are stipulated in new construction [244], contracts need adaptation for
existing buildings due to e.g. owners responsibility for legacy. Furthermore, responsibility of model
and content management during maintenance seems not to be addressed in literature and legal
frameworks yet, although updated BIM content is crucial for any maintaining, retrofitting or
deconstruction planning.
4.4.3 Education and Training, Culture
Although BIM is spreading in AEC industries worldwide, the need for qualified personnel remains a
bottleneck of BIM implementation in new buildings [7,9,11,36,67,230]. Other major hindrances are the
willingness to collaborate and cultural differences [16]. A comparative study on BIM in education
identified a need for alignment of training contents, academic education and industry requirements,
but relativized their statement through the rapid technological changes in this area [246].
Facility managers, owners of existing buildings, deconstructors and consultants are scarcely using
BIM [15,16] and are not fully integrated in BIM development and implementation yet [15]. Thus, there
is a need to enhance their integration, training and education to maintain, use and also deconstruct (if
needed) the rising number of complex BIM-constructed or BIM-retrofitted buildings and infrastructures.
5 Discussion of findings and future needs
Considering BIM for existing buildings and related maintenance and deconstruction processes, we
reviewed more than 180 academic and applied publications from journals, conference proceedings
and other sources of professional associations, standard committees and authorities. Numerous rapid
changes and recent developments not only push implementation and research in many BIM-related
areas [8], but also enlarge the complexity of research. Thus, some publications or trends might have
been overlooked and not been considered in this paper.
Due to the former development of BIM, architects, engineers and contractors played a major role as
early adopters of BIM technology and still dominate the elaboration of BIM functionalities [15] and
dissemination [7]. Although on the one hand, implementation of BIM both in new and existing buildings
induces profound changes of processes and information flows (e.g. through IPD), on the other hand it
accrues considerable advantages (e.g. in risk mitigation or improved data management). Recently,
research turns to FM requirements, but still it is mainly focusing on new or recently completed
buildings with a building information model (BIM) at hand, rather than on existing buildings without BIM
[8,29]. Besides, owners, facility managers, deconstructors and related consultants are hardly involved
in the BIM functionality development yet [15]. Thus, existing buildings requirements such as e.g.
cause-effect and deterioration modeling [99], deviation modeling [130] or uncertainties are not
considered yet.
In the following, we discuss not only major potential benefits of BIM implementation in existing
buildings that could be implemented, but also challenges, process changes and resulting research
Functional issues: If BIM is used for FM in new buildings, clear benefits are reported e.g.
regarding improved information flows and project management, risk mitigation and positive return
on investments [11] especially in complex structures. BIM in FM or deconstruction is not used
industry-wide yet, but potential functionalities of BIM in existing buildings for FM [11] and
deconstruction are numerous. Many FM approaches already benefit from BIM information of
recently built structures e.g. through performance monitoring [7], or virtual reality [233]. Yet, only
few approaches deal with deconstruction planning [2,24] or vulnerability and collapse analyses
[146,154], assuming a preexisting BIM that contains the required information. But further expert
refurbishment or deconstruction processes might also benefit from BIM usage through
improved/supported decision-making in complex facilities, shortened refurbishment or
deconstruction schedules, reduced costs, jobsite safety during deconstruction, enhanced
collaboration, documentation, data management and visualizations (e.g. during bidding or
renegotiations). Ecological issues are not accounted for, like resource efficiency, potentially
achievable recycling qualities or recycling rates (recyclability), ability of dismantling component
connections, separability of material layers and composites, deconstructions ' emissions or
immissions (such as noise, dust, vibrations), or respective protection measures that could be
simulated or optimized through BIM.
If BIM is implemented in existing buildings, it might also affect sustainability ratings and
certifications. Although some sustainability ratings already include some end-of-life considerations
[247,248], BIM might be used to integrate monitored values such as energy consumption, waste
water, or maintenance costs into their rating or to extend current assessment criteria with regard to
recyclability or other end-of-life considerations on component level. These adaptions would help to
enlarge the depicted environmental effects of a built structure and to verify and monitor
consumption and emission values of certified structures.
As the development of maintenance functionalities requires standardized Levels of Detail resp.
Development (LoD) of BIM content, COBie standard is an important milestone for BIM use in FM.
Although COBie includes material and sustainability information, it excludes information on
architectural parts such as slabs, walls, footing, roof, ramps and stairs that are essential e.g. for
refurbishment or deconstruction planning. Also, flow segments and fittings are not included in
COBie, but are relevant e.g. during maintenance, deconstruction and separation of components
and materials. For deconstruction-related functionalities no LoD is defined yet, and process and
interaction maps for information exchange in BIM are lacking. This is hampering interoperability
and information exchange in ‘as-built’ BIMs. Besides, the many coexistent concepts for assessing
BIM model quality (e.g. LoD, Object/Element Matrix, or CMM) might benefit from harmonization.
Although the use of BIM in existing buildings might contribute to better project and data
management, it is confronted with major shortcomings. As BIM use in existing buildings is only
appropriate with precise, unambiguous and relevant up-to-date information [3], BIM data quality is
crucial to any applied functionality. Major challenges and areas of research are therefore on the
one hand the initial data capture and automated BIM creation [62,63,151,152] (see section 4.3) and
on the other hand the information maintenance and assessment in BIM [7,11,21] (see sections
4.1.2 and 4.4). A third major issue is the handling and modeling of uncertain data, objects and
relations occurring in existing buildings, which is not addressed in BIM yet. To cope with these
issues and to reduce time and cost, the integration of monitoring and capturing methods into BIM
seems promising to keep BIM information automatically up-to-date. Further development of
attributes and integration of techniques like semantic reasoning is essential to provide
unambiguous attribute definitions and to improve the capture and processing of building
information, allowing future FM and deconstruction functionalities. This will help to ensure
interoperability between BIM and attached expert functionalities and to facilitate BIM
implementation in existing buildings.
Informational issues: Incapable interoperability still is a major obstacle in BIM data exchanges
both in new and existing buildings. To increase interoperability, universal data structures are
developed continuously. But developments focus on new rather than existing buildings and their
requirements yet [180]. Some developed concepts (IDM, MVD) were recently specified for expert
functionalities in new or recently constructed buildings, e.g. for energy analysis or for FM. But to
enable data exchange with e.g. potential decontamination planning or deconstruction progress
tracking functionalities, both concepts require further specifications. Besides, MVD are not
available for the actual IFC2×4 format yet [249]. As long as research focuses on recently built
structures and their requirements, the development of standards will be slow and hamper BIM
implementation in existing buildings.
The second informational challenge results from the outpacing BIM technology development. Due
to long lifetimes of buildings and infrastructure, challenges arise from interoperability within the
rapidly developing BIM models, expert functionalities and continuous model maintenance during
building lifetime [11,12,37]. Besides, due to increased demand for semantic web technologies
[12,67,179], mobile BIM and cloud computing [34,120,231,232] that further enhance applicability of
BIM, challenges are to be met in management of temporal data, transaction management and
synchronization in BIM [11,12,37,150].
Technical issues: If building documentation is inadequate for maintenance or deconstruction
processes, capturing and surveying techniques with different qualities are applied to audit and
gather existing buildings’ characteristics. The functionality-related Level of Detail (LoD) and the
corresponding data capturing technique influence all following steps of BIM creation and its
associated effort, e.g. surveying and processing times [4].
Due to a mainly interactive and time-consuming data capturing, processing and creation process,
BIM modeling effort is high and thus BIM is often not applied in existing buildings yet. Besides, a
high LoD e.g. required for detailed maintenance or deconstruction considerations is not compatible
with current time or cost restrictions in the AEC/FM/D sector.
Resulting major research challenges are (1) effort reduction (automation) of capturing, processing,
recognizing and ‘as-built’ BIM creation anew [4,31,43,45,62,77], (2) capturing and integrating
semantic information into BIM [6,43,45] as well as (3) addressing of technique-specific restrictions
e.g. such as environmental influences in field operation [64,130] or post-processing of concealed,
distorted, structural or semantic building information [19]. Therefore, approaches focus on the
development of cost-efficient and highly automated BIM creation based on laser scanning or
photogrammetry. But future research approaches could also include material- or texture-based
recognition [151] and non-destructive testing methods such as ground penetrating radars,
radiography, magnetic particle inspection, sonars or electro-magnetic waves [205] or tags installed
during retrofits to increase information richness in BIM. Further automation of modeling semantic
and volumetric BIM objects from captured data [6,43,45] might be achieved through specific but yet
unavailable object libraries of real building components, learning algorithms [31], testing in real
environments [31,66], consideration of uncertainties, and further detailing through capturing small,
concealed or non-planar components in complex buildings [31,82,190]. The recognition and
modeling of installations, ducts and pipes (HVAC/MEP) might e.g. benefit from similar approaches
in other industries [214,222]. Apart from that, BIM applications on mobile devices are increasingly
demanded, but yet face high data volumes and computing times [64,130].
Organizational and legal issues: With the spreading of BIM in the AEC/FM/D communities,
traditional processes and stipulations are adapted at different speed and scope to digitally
supported collaboration through BIM. Political pressure in countries like UK or USA furthers
implementation of BIM [236,237] e.g. through public tendering, while developments in other
countries’ construction sectors are lagging behind. Thus, organizational and legal BIM frameworks
vary in different countries and in application in new or existing buildings, but different stages of
development are not reported or examined in literature yet.
Although some sources describe a lacking industry-wide collaboration due to resistances and lack
of training [7,11,67], BIM collaboration is spreading [150]. Recently, capable collaboration systems
are developing [150] yet focusing on content management, viewing and reporting rather than on
model creation or system administration. And further capacity developments in this area are
expected to facilitate BIM implementation e.g. through cloud computing, sensor networks or
semantic web approaches [150,179].
As BIM implementation demands profound process changes [7], it has great implications on
contractual relationships in AEC/FM/D industry. In recent years, legal instruments and contractual
agreements in the AEC/FM/D industry on BIM were not widely adapted [130,153,250,251]. But
lately, institutions and professional associations in leading countries provide contract templates and
legal advice for stakeholders in new building projects. As stakeholders, their interests and required
processes (e.g. bidding and procurement) vary from planning and construction to maintenance and
deconstruction LC stages, adaption of legal frameworks would be necessary if BIM is applied in
existing buildings. Besides, an interdisciplinary education of facility managers, deconstructors and
consultants might be necessary to implement BIM in existing buildings. But as long as issues of
model ownership and data responsibility, LoD, liabilities and fees are not stipulated or standardized
[11], it will hinder BIM implementation in existing buildings due to reduced data security and user
confidence [17].
6 Conclusion
The conducted literature review of over 180 publications presented the state-of-the-art implementation
and research of building information models (BIM) in existing buildings with focus on maintenance and
deconstruction LC stages. Due to the former BIM development, architects, engineers and contractors
play a major role as early adopters of BIM technology and still dominate the elaboration of BIM
functionalities [15] and BIM dissemination [7]. Despite the increasing BIM usage in new structures,
implementation of BIM in existing buildings is still limited yet, focusing on recently completed buildings
with a BIM at hand rather than on existing buildings without BIM [8,29]. But research approaches are
intensifying to harness BIM for application in existing buildings and to capture and integrate building
data into BIM. A growing number of maintenance interfaces and functionalities in preexisting BIM are
developing for recently constructed buildings, while applications and research approaches for
deconstruction functionalities in BIM remain rare and do not cover all related aspects. Owners, facility
managers, deconstructors and related consultants are hardly involved in BIM functionality
development yet [15].
Although on the one hand, implementation of BIM both in new and existing buildings induces profound
changes of processes and information flows (e.g. through IPD), on the other hand it accrues
considerable advantages. Potential BIM functionalities and benefits in existing buildings are
numerous. Calculation of alternatives and optimizations seem promising to enhance project
management and risk mitigation or to limit costs and duration of FM or deconstruction measures, e.g.
in complex buildings or infrastructures. Onsite progress tracking, measurements and monitoring
through cloud computing depict potential future trends of automated capture and transformation of
building information into BIM. Besides, stricter regulations on rubble management and increasing
product responsibilities of manufacturers might lead to BIM-based monitoring of (hazardous)
components and to increased interest in information on existing buildings, related sustainability
properties, reuse/recycling options or emissions (e.g. through LCA). Other important FM and
deconstruction requirements such as e.g. cause-effect and deterioration modeling [99], deviation
modeling [131] or uncertainties are seldom considered yet. To implement such functionalities, a
structured and integrated data repository on building information like BIM could be beneficial to
authorities, decontaminators, deconstructors or industry professionals.
Our findings reveal that major challenges and areas of research are (1) the automation of data capture
and BIM creation (without preexisting BIM), (2) the update and maintenance of information in BIM and
(3) the handling and modeling of uncertain data, objects and relations occurring in existing buildings in
BIM. New data capturing techniques try to overcome lacking building information at low costs. But
current approaches face challenges of capturing structural, concealed or semantic building information
under changing environmental conditions and of transforming captured data into unambiguous
semantic BIM objects and relationships. Less dominant challenges are varying quality assessments of
BIM models, undefined LoD for deconstruction functionalities, interoperability between BIM models of
different generations and underdeveloped object properties and processes for maintenance and
especially deconstruction purposes.
Adaptation of BIM-related legal and organizational frameworks differs between countries. Progressive
AEC/FM/D industries (e.g. UK, USA) reformed national regulations and implemented novel
collaboration processes through BIM, but rather for new than for existing buildings. Organizational and
legal issues seem to be major levers to influence BIM implementation due to their coherences of BIM
in a broader sense. But to our knowledge there is neither research on the worldwide spreading of BIM
and its related changes of processes and regulations in different circumstances nor a comprehensive
cost-benefit analysis of BIM implementation for existing buildings yet.
Fast developments of BIM and the recent release of standards such as COBie or IFC 2×4 are
promising for future process automation, alignment of BIM with AEC/FM/D processes and efficient
resource management through BIM in new and existing buildings. Longtime trends like the increased
digitalization and automation, growing existing building stocks and sustainability requirements, as well
as emerging technologies like cloud computing, semantic web technology and mobile BIM devices will
stimulate and extend BIM implementation in existing buildings. But due to the revealed state-of-the-art
BIM implementation in existing buildings, this area has many challenging future research opportunities
at hand.
We would like to thank the anonymous reviewers for their recommendations that improved the
comprehensiveness and clarity of our paper. This paper was inspired during the preparatory research
for the project ResourceApp (#033R092) funded by the Federal Ministry of Education and Research
(BMBF) in Germany. Because of synergies between paper and project, we like to thank André Stork,
Neyir Sevilmis, Jörg Woidasky, Christian Stier and the other project partners as well as Karoline Fath
and Michael Hiete for the good collaboration.
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... A BIM model can be defined as a digital representation of the physical and functional characteristics of a facility [16,28]. The major difference between BIM and traditional threedimensional computer-aided design (3D CAD) is that a BIM model can contain building materials information as well as construction stage data while 3D CAD tools cannot [29]. Today, building owners have demanded that after the completion of a facility's construction work, contractors or engineering consultants prepare and finalize the corresponding as-built BIM model [30]. ...
... From a theoretical point of view, a building can be represented by BIM elements or components, such as floor levels, rooms, doors, windows, and walls [29,35]. These BIM elements can have spatial relationships with each other, such as a floor level BIM element can contain several room BIM elements, and a room BIM element can contain several BIM elements such as doors, windows and walls [29]. ...
... From a theoretical point of view, a building can be represented by BIM elements or components, such as floor levels, rooms, doors, windows, and walls [29,35]. These BIM elements can have spatial relationships with each other, such as a floor level BIM element can contain several room BIM elements, and a room BIM element can contain several BIM elements such as doors, windows and walls [29]. All such BIM elements can contain attributes describing building materials utilized [29]. ...
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As our society ages, more and more elderly or disabled people live in long-term care (LTC) facilities, which are vulnerable to fires and may result in heavy casualties. Because of the low mobility of LTC residents, firefighters often need to enter the facility to save people. In addition, due to LTC facility management needs, many doors or windows on the passages for a fire rescue operation may be blocked. Thus, firefighters have to employ forcible entry tools such as disk cutters for passing through, which may lengthen the rescue time if an incorrect route or tool is utilized. As new information technologies such as ontology and building information modeling (BIM) have matured, this research aims at proposing a BIM-based ontology model to help firefighters determine better rescue routes instead of using rules of thumb. Factors such as the path length, building components and materials encountered, and forcible entry tools carried are considered in the model. Real LTC fire investigation reports are used for the comparisons between the original routes and the ones generated by the proposed model, and seven experts joined the evaluation workshop to provide further insights. The experts agreed that using the proposed approach can lead to better fire rescue route planning. The proposed BIM-based ontology model could be extended to accommodate additional needs for hospital fire scenes, in the hopes of enhancing the efficiency and effectiveness of firefighters’ rescue operations in such important facilities.
... [1] For the majority of the bridges currently in use, however, an as-is model does not exist. [2] Since the manual and retrospective modeling of these structures is a demanding task even for expert engineers [3], current research aims at the full or partial automation of the task. The geometrical aspect of the model is mostly dealt with by the acquisition and processing of point clouds, images or construction plans. ...
... A CRF infers token labels based on the conditional probability that a label occurs given the neighboring labels, thus, it takes the context into account. In the course of this study, multiple model architectures are tested for the sequence tagging: (1) a CRF, (2) an LSTM, (3) an LSTM + CRF layer, (4) a Bi-LSTM, (5) a Bi-LSTM + CRF layer, and (6) a Bi-LSTM followed by another LSTM and a CRF layer. As a classification layer, a fully connected (FC) layer is inserted after the LSTM layers. ...
... The The user interface is depicted in Figure 4 and aids the engineer as follows: The information extraction pipeline takes a bridge record as input and outputs a CSV file. The user imports the file via the GUI (1) and proceeds with the selection of parameters and their respective values to be imported (2). The GUI snippets (4) and (5) depict the created and the enriched element parameters of the model (3), respectively. ...
Conference Paper
Full-text available
The majority of innovative approaches in the realm of the retrospective generation of building information models for existing structures deal with geometry extraction from point clouds or engineering drawings. However, many building-specific or object-specific attributes for the enrichment of building models cannot be inferred from these geometric and visual data sources, and thus their acquisition requires the analysis of textual building documentation. One type of such documents are structural bridge records, which include specifications regarding used material, location, structural health, modifications, and administrative data. The documents are semi-structured and hardly allow a robust information extraction based on traditional programming, since the implementation of such an approach would result in a complex nesting of conditional clauses, which is not guaranteed to remain effective for future versions of the document structure. Therefore, a data-driven approach is adopted for the information extraction. This paper demonstrates an end-to-end semantic enrichment method, taking a bridge status report as input and feeding structured object parameters directly to the building information modeling software for the enrichment of the model. The proposed method requires little user interaction and achieves production-ready accuracy. It is tested on an as-built model of an actual bridge and shows promising results.
... Virtual design and construction (VDC) approaches (Dawood and Sikka 2008;Eastman et al. 2009;Han, Law, and Kunz 2000;Haymaker et al. 2004;Khanzode, Fischer, and Reed 2008) have demonstrated the benefits of visualisation, simulation, and process automation to enable better control and transparency of project execution in the AEC domain. Early-stage simulation methods are particularly known to be useful tools to identify optimised renovation scenarios in terms of cost and time (Kemmer and Koskela 2012;Volk, Stengel, and Schultmann 2014;Chaves et al. 2017). They also allow to reduce renovation uncertainty, assessing the performance of different renovation approaches and strategies and assisting decisionmaking processes (Sacks, Treckmann, and Rozenfeld 2009). ...
... It allows better visualisation, communication and decision-making through 3D-based simulations of several renovation scenarios and strategies (Charles O. Egbu 1997;Papamichael 1999;Sheth, Price, and Glass 2010). Despites all these advantages and benefits, research works are still lacking on the use of BIM (Joblot et al. 2019) and simulations in renovation (Kemmer and Koskela 2012;Volk, Stengel, and Schultmann 2014;Chaves et al. 2017), especially for hazard identification and risk mitigation. This paper shows how using BIM alongside AI tools enables representation, in a machine readable format, and automatic processing of the massive amount of hazard knowledge that are increasingly obtainable through project feedback, human expertise, to name but a few. ...
Conference Paper
Full-text available
The delivery of construction projects in general can be complex and demanding, and presents well-documented challenges to the control of cost, safety, and quality. This situation becomes even more challenging in the case of renovation projects due to the high level of interaction with occupants, especially when they remain in the building over the renovation period. The safety of project participants as well as that of occupants when they are present in the renovation site must be ensured. Although the planning and management of such projects can be greatly enhanced by exploiting some of the advantages of Building Information Modelling (BIM), the process of construction hazard identification and renovation scenarios assessment is still human-based and so requires considerable time and effort. Moreover, there is little research that addresses how hazard identification can best be represented and processed automatically in order to optimise and develop more effective strategies for managing construction projects, particularly those involving the systematic renovation of existing properties for better energy performance. Using BIM along with Artificial Intelligence (AI) tools could help in processing the massive amount of newly-available data and knowledge (e.g., feedback, images captured from smart devices, IoT sensors) that are increasingly obtainable. A prerequisite for doing so is the development of a dedicated ontology that would enable the formalisation of domain knowledge, including associated concepts, relations, and constraints that are specific to renovation project hazard. The authors propose an ontology and demonstrate its application by developing a knowledge-based system for application within the context of deep renovation projects that are part of a large European research project: the RINNO project.
... For these bridges, no BIM model exists, which is a prerequisite for the application of DIM. A number of studies have been conducted in the domain of 3D model generation of existing buildings via point clouds (Volk et al. 2014;Barazzetti et al. 2016;Kropp et al. 2018). In accordance with such as-built models, damage information could be added to extend the use of BIM for inspection and assessment. ...
Bridges are designed to last for more than 50 years and consume up to 50% of their life-cycle costs during their operation phase. Several inspections and assessment actions are executed during this period. Bridge and damage information must be gathered, digitized, and exchanged between different stakeholders. Currently, the inspection and assessment practices rely on paper-based data collection and exchange, which is time-consuming and error-prone, and leads to loss of information. Storing and exchanging damage and building information in a digital format may lower costs and errors during inspection and assessment and support future needs, for example, immediate simulations regarding performance assessment, automated maintenance planning, and mixed reality inspections. This study focused on the concept for modeling damage information to support bridge reviews and structural analysis. Starting from the definition of multiple use cases and related requirements, the data model for damage information is defined independently from the subsequent implementation. In the next step, the implementation via an established standard is explained. Functional tests aim to identify problems in the concept and implementation. To show the capability of the final model, two example use cases are illustrated: the inspection review of the entire bridge and a finite-element analysis of a single component. Main results are the definition of necessary damage data, an object-oriented damage model, which supports multiple use cases, and the implementation of the model in a standard. Furthermore, the tests have shown that the standard is suitable to deliver damage information; however, several software programs lack proper implementation of the standard.
... Information Modelling (BIM) is an integrated infrastructural data management process that shares and increases the transparency of building data in its designing, construction, and management (Ghaffarianhoseini et al., 2017;Volk, Stengel, and Schultmann, 2014 ...
Conference Paper
Full-text available
The smart built environment (SBE) exhibits a dynamic integration between the physical and digital environment, where the physical elements, such as spaces, walls, windows, doors, roof, and floor, interacts with the digital sensing elements, such as sensors, actuators, control systems, and networking systems. Energy neutrality is a concept dealing with the lifecycle energy performance of energy-saving sensing devices integrated into the SBE, such as the smart sensors-actuator system (SSAS). Ontology is a concept of representing and organising information (and their interrelationships) about a specific domain with an intent to manage complexity, enhance understanding, and promote problem-solving skills. Employing semantic web technologies, a framework for designing and simulating energy-neutral, sensor-embedded smart buildings is proposed that exhibits an ontological integration of Lifecycle Assessment (LCA), Building Information Modelling (BIM), and Product Lifecycle Management (PLM). A preliminary implementation of the proposed framework is demonstrated using OWL (Ontological Web Language) in the Protégé software. After that, a design interaction matrix between buildings (and their components), building designers, product designers, and lifecycle practitioners is developed to provide efficiency, optimisation, and sustainability in the design process. This integration framework would streamline the design process, providing a collaborative simulation platform for cross-field designers to enhance the environmental performance of the SBE. In the future, this framework could be employed to create a robust real-time integrated IoT-based platform for designing and modelling energy-neutral smart buildings.
The progress in information technology allows an innovative transformation of practices commonly involved in the engineering and construction field, especially in relation to the existing architectural heritage's control and management activities. The proposed methodology takes advantage of an integrated 3D metric survey as a basis for an HBIM (Historic Building Information Modelling) model to be exploited for the definition of a Finite Elements Model (FEM). This paper aims to show the applicability of a digital process, stemmed from the integration in Rhinoceros 3D of a BIM structural model, leading to the dynamic simulation of the analytical FEM through PRO_SAP® (a PROfessional Structural Analysis Program). The described workflow investigates the interoperability issues, along with the difficulties in the Scan-to-HBIM processes, demonstrating how HBIM models can anyhow support operations aimed at maintaining and preserving existing historical assets, also from a structural point of view, even if with still persistent criticalities.
Historic Building Information Modeling (HBIM) and BIM Collaboration Format (BCF) offer new possibilities for recording damage and pathologies, since semantic data can be associated with a BIM model. This study investigates the potential of HBIM for the diagnostic documentation of modern cultural heritage via a case study carried out in the E1 Building, at the University of São Paulo, Brazil. Aiming at a Diagnostic Model, this study investigates the use of BCF rather than a Damage Map produced in two-dimensional representation systems. A BCF platform was chosen to evaluate the available resources and their limitations. The main contribution of this research consists in showing that BIM use is feasible to develop diagnostic documentation. Although not all expected functionalities were identified in the selected platform, we confirmed that BCF is an open data format with the potential to semantically enrich an HBIM model. For future research projects, guidelines are suggested for developing specific HBIM software for the diagnostic documentation of cultural heritage.
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Highlights:  This paper illustrates the potential of scan-to-HBIM notion for heritage sites by employing an innovative data-driven approach to conservation actions.  This research offers an HBIM workflow for the sophisticated representation of heterogenic archaeological datasets.  This study creates a digital twin of the archaeological building remains and offers a method tailored for future monitoring and conservation. Abstract: Digital surveying tools provide a highly accurate geometric representation of cultural heritage sites in the form of point cloud data. With the recent advances in interoperability between point cloud data and Building Information Modelling (BIM), digital heritage researchers have introduced the Heritage/Historic Information Modelling (HBIM) notion to the field. As heritage data require safeguarding strategies to ensure their sustainability, the process is closely tied to conservation actions in the architectural conservation field. Focusing on the intersection of the ongoing trends in HBIM research and the global needs for heritage conservation actions, this paper tackles methodological pipelines for the data-driven management of archaeological heritage places. It illustrates how HBIM discourse could be beneficial for easing value-based decision-making in the conservation process. It introduces digital data-driven conservation actions by implementing a novel methodology for ancient building remains in Erythrae archaeological site (Turkey). The research ranges from a) surveying the in-situ remains and surrounding stones of the Heroon remains with digital photogrammetry and terrestrial laser scanning to b) designing a database system for building archaeology. The workflow offers high geometric fidelity and management of non-geometric heritage data by testing out the suitability and feasibility for the study of material culture and the physical assessment of archaeological building remains. This methodology is a fully data-enriched NURBS-based (non-uniform rational basis spline) three-dimensional (3D) model-which is integrated and operational in the BIM environment-for the holistic conservation process. Using a state-of-the-art digital heritage approach can be applied from raw data (initial stages) to decision-making about an archaeological heritage site (final stages). In conclusion, the paper offers a method for data-driven conservation actions, and given its methodological framework, it lends itself particularly well to HBIM-related solutions for building archaeology. Keywords: building archaeology; digital archaeology 3D heritage database; conservation decisions; Historic Building Information Modelling (HBIM); NURBS (non-uniform rational basis splines); scan-to-HBIM Resumen: Las herramientas topográficas digitales proporcionan una representación geométrica muy exacta de sitios patrimoniales en forma de datos (nubes de puntos). Con los avances recientes de interoperabilidad entre nubes de puntos y modelado de información de la construcción (BIM), los investigadores en patrimonio digital han introducido la noción de modelado de información de la construcción patrimonial/histórica (HBIM) en este campo. Como los datos patrimoniales requieren estrategias de salvaguardia que garanticen su sostenibilibidad, el proceso está íntimamente ligado a acciones de conservación en el campo de la conservación arquitectónica. Teniendo en cuenta las últimas tendencias en investigación HBIM y las necesidades globales de las acciones de conservación patrimonial, este artículo afronta el flujo metodológico de la gestión basada en datos de sitios patrimoniales arqueológicos. Se introducen acciones de conservación basadas en datos que implementan una metodología novedosa en los restos edificados del sitio arqueológico de Erythrae (Turquía). La investigación aborda tanto la fase desde a) el topografiado in situ de los restos y las piedras circundantes de los restos de Heroon con fotogrametría digital y escaneado láser terrestre, hasta b) la fase del diseño del sistema de bases de datos en arqueología de la arquitectura. El flujo de trabajo ofrece alta fidelidad geométrica y de gestión de datos patrimoniales no geométricos; también prueba la idoneidad y viabilidad de cara al DATA-DRIVEN CONSERVATION ACTIONS OF HERITAGE PLACES CURATED WITH HBIM Virtual Archaeology Review, 13(27): 17-32, 2022 18 estudio de la cultura material y a la evaluación física de los restos de edificios arqueológicos. El modelo tridimensional (3D) enriquecido con datos basados en NURBS ('non-uniform rational B-splines'), se demuestra que es operativo en el proceso de conservación integral; este trata desde los datos sin procesar hasta la toma de decisiones sobre un sitio arqueológico-patrimonial, utilizando un procedimiento digital puntero. En conclusión, el artículo presenta un método orientado a acciones de conservación basadas en datos y, dado su marco metodológico, se presta particularmente bien a soluciones relacionadas con HBIM en arqueología de la arquitectura. Palabras clave: arqueología de la arquitectura; bases de datos patrimoniales 3D; decisiones de conservación; modelado de información de la construcción histórica (HBIM); NURBS (B-splines racionales no uniformes); escaneado-a-HBIM
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Residential building inspections are periodically required by public authorities. However, current approaches to storing and viewing data concerning an inspection are often collected in reports whose form and limited content hamper the rigorous assessment of the building's state of conservation and subsequent repair of the identified damage and alterations. This research proposes a method for documenting and displaying inspection-related information in BIM models to generate a dynamic information model. Damage is spatially located by means of a parametric family, which collects the necessary information about each instance of damage and enables agile and up-to-date information extraction. The proposed method was validated in a residential building situated in San Sebastián, with a scenario designed to demonstrate its ability to support the diagnosis of causes and decision making regarding maintenance. This work demonstrates the advantages of the parametric representation of information on damage and alterations in a BIM model, which facilitates the management of a residential building's life cycle by means of a digital twin of the building. The results shown in this research may be very interesting for researchers as well as for those whose work involves the rehabilitation of residential buildings.
Mitte der 90er Jahre machte sich in Deutschland ein aus den USA stammender Begriff breit: Facility Management (FM). Zunächst nur wenigen Insidern bekannt, mauserte sich dieser Begriff zu einem breit diskutierten innovativen Managementansatz.