Development of knowledge model for construction projects Andrej Tibaut1 and Denis Jakoša2 1
University of Maribor, Faculty of Civil Engineering, Maribor, Slovenia
[email protected] 2 University of Maribor, Faculty of Electrical Engineering and Computer Science, Maribor, Slovenia
[email protected]
Abstract. The growing need for interoperability and the use of BIM (Building Information Modeling) within the AEC domain (Architecture, Engineering and Construction) is leading to the increased need for efficient knowledge management. In order to digitally manage and understand large volumes of information contained in construction works projects, the paper suggests a knowledge engineering approach with a common knowledge model. The new knowledge model (ontology) for AEC domain is presented and applied as a case study in a real construction project. As a result, a more effective knowledge management throughout the whole lifecycle of AEC projects is expected.
Keywords: knowledge management · BIM · ontology · construction project
1
Introduction
Companies that have survived the economic crisis of the construction industry share belief in the importance of knowledge management in construction projects. In consequence the belief results in requirements for a more effective course of a construction project such as • requirements for a more comprehensive management of data flow in construction projects by introducing an integrated information model (BIM) and • requirements for more efficient knowledge management in the lifecycle of construction object. The first requirement relates to the current culmination of an understanding of management of information throughout the lifecycle of a construction project (planning, design, engineering, construction, operations and maintenance), where stakeholders (architect, MEP and HVAC design engineer, structural engineer, quantity surveyor, suppliers, construction manager, site foreman, site supervisor and facility manager) traditionally communicate their documentation (data models), at best, as cumulative
layered 2D CAD (DWG) drawings (schemas) or in worst case as PDF documents. The drawings (Fig. 1) for floor plans contain only drawing primitives in form of points and lines (plane XY) without elevations. The drawings (Fig. 2) for section plans (plane XZ and YZ) contain elevations but only for predefined cross-sections of the construction object. Therefore multiple 2D CAD drawings must be consulted in order to perceive construction object in its 3D entirety. Finally, the semantics (description, physical dimensions, construction details, manufacturer, etc.) of the drawing primitives can be expressed with text-annotations only. The characteristics of the yet prevailing design and engineering work practices throughout the lifecycle of a construction object, which are relevant to the knowledge engineering, can be summarized as follows: • Construction projects are fragmented among numerous stakeholders, which is also stated by other authors [1]. • Engineering designs in form of 2D CAD plans lack of an integrated information model. • Information that is exchanged between stakeholders in the construction process does not necessarily have an understood meaning. • Use of the weak knowledge assets results in lengthy procedures for preparation and coordination of the construction projects and, consequently, in unplanned costs due to limited digital interoperability between construction project stakeholders. The Fig. 3 shows unplanned cost as they are shared throughout the lifecycle of a construction object.
Fig. 1. Heating, Mechanical & Plumbing floor plan: drawing primitives with implicit semantic [13]
The aforementioned characteristics are believed to disadvantage the efficiency of construction industry in comparison to other engineering disciplines (i.e. automotive industry). Therefore a new work paradigm in construction industry, the Building Information Modeling - BIM [5][11], is heavily influencing research and practice in construction industry. BIM could provide an ideal platform for integrated practice since it is capable of integrating and linking the project information to the data level [8].
Fig. 2. Predefined section plan of a building: drawing primitives with implicit semantic [13]
The second requirement concerns the need for more efficient knowledge engineering in the lifecycle of construction object. Young civil engineers lack knowledge about the workflows in the lifecycle of a construction project but they demonstrate a good working knowledge of information and communication technology. In an effort to perform cost-effective and to meet economically reasonable deadlines for the construction project, all project stakeholders strive for the timely completion of works. In such circumstances experienced engineers (i.e. site foreman) practically do not have time to guide younger less experienced engineers (i.e. assistant site foreman) through the daily workflow activities (i.e. on construction site) in order for them to understand “why and how” [12]. To facilitate the knowledge exchange in construction project between experienced and less experienced engineers better personal knowledge management in connection to organisational knowledge management is required [4]. Inefficient digital interoperability leads to a non-existent or interrupted flow of information between stakeholders in the construction process (Fig. 4a). Interruption of the information flow results in the repetition (i.e. architect and structural engineer do
not share integrated building model, instead they both create one for themselves) and high chance of errors.
Fig. 3. Unplanned cost share because of inefficient digital interoperability in construction [7]
According to research [6] 86% of public works projects end up with cost overruns. Some unexpected findings of the research were that: • Technically difficult projects were not more likely to exceed the budget than less difficult projects. • Projects in which more people were directly and indirectly affected by the project turned out to be more susceptible to cost overruns. • Project managers generally did not learn from similar projects attempted in the past. More efficient knowledge management in the construction processes is possible with common server based information model (BIM server, Fig. 4b). Such server stimulates an overall collaborative environment based on a common reference data model for AEC industry. Apart from existing commercial server based solutions, a viable and open source solution is BIMserver.org [2]. BIMserver.org’s functionality includes selection, update, and deletion of (sub)models of a construction object (i.e. an archi-
tectural model, a model of mechanical installations) and it also conforms to the specification of Industry Foundation Classes (IFC) [9].
Fig. 4. a) Typical (interrupted) information flow in construction project. b) Information flow integrated with Building Information Model (designed by authors).
2
Case study: knowledge model for a construction project
The growing need for interoperability and the use of BIM within the AEC domain is leading to the increased need for efficient knowledge engineering and management systems. In order to control, manage and understand large volumes of information in the two current (2014, 2015) infrastructure construction projects “Underpass Grlava” and “Underpass Ljutomer”, which are carried out within the project named “Electrification and reconstruction of the railway line Pragersko – Hodoš”, we have looked for solutions in knowledge modelling and semantic technologies. On the Fig. 5 the construction site of the construction project “Underpass Grlava” is shown. As part of our case study methodology we have decided to investigate common characteristics of the two construction projects. This can be best achieved with existing technical documentation (i.e. consultants’ technical report). The technical documentation summarizes all important facts about the construction project. For the application of semantic technologies we have decided because the two construction projects have the following characteristics: • A large amount of construction data for “Underpass Grlava” and “Underpass Ljutomer” (technical report, detailed design plans, construction schedule plan) that we want to model syntactically and semantically; • Technical reports for both projects contain rich, but non-uniform and hard-torelate, structure and technical terminology, which are the results of the work of two different designers (i.e. use of the term "tact" and "lamella" for a scheduled zone on the construction site). We want to align the available data from the technical report at the level of the common concepts.
Fig. 5. Construction site “Underpass Grlava”: use case for application of knowledge model
As a result, we expected a more effective management of knowledge on the project’s construction site. The project involved one structural design engineer and one draughtsmen working in the engineering consultancy office, a project manager, site foreman/manager, assistant site foreman, several labourers, specialists and sub-contractors working onsite. At first we had to develop a knowledge model that defines the structure of the data using an open source ontology editor and framework for building intelligent systems Protégé. While creating a knowledge model we relied on a standardized data dictionary initiated by BuildingSmart [3]. The result was a general knowledge model (ontology) that can be universally applicable in AEC projects.
3
Knowledge model – construction ontology
For the purpose of this assignment Protégé, a semantic knowledge technology, was used to create a knowledge model which has completeness, connectedness, congruency, perspective and purpose. Transformation of knowledge, contained in the construction project, to ontology started with the two technical reports (project design description document) produced by project consultants (civil engineers). The technical reports were used to identify most relevant concepts in the construction project (Fig. 6). First the two documents
were compared according to their table of contents in order to align the conceptually similar chapters (i.e. description of the construction object) and their related chapters were aligned first. In the next step most relevant (and frequent) terms were identified as candidates for common concepts in the planned ontology.
Fig. 6. Knowledge model: concepts hierarchy
These concepts were defined in a class hierarchy and the various classes and concepts were linked via object properties and data points were set for various members using the data property functionality (Fig. 7). Knowledge taxonomy is also a vital part of the knowledge model. A knowledge model fails if a common understanding and structure is not initially reached and understood. For the purpose of this assignment the buildingSMART Data Dictionary was used for the taxonomy, aiding in the achievement of externalisation.
Fig. 7. Knowledge model: object properties
The resulting knowledge model (semantic network), a construction ontology is presented on Fig. 8.
Fig. 8. Ontology graph: main concepts in the construction ontology
Visualisation of construction ontology shows semantic network links between various concepts created as part of the ontology. The main concepts subgroups are Project,
Contract, Materials, Construction Site, Construction, Project, Design, Structural Design, type of Design and Design Codes. Fig. 9 shows links created between concepts of Contract, Subcontract, Contracting Parties, Contractor and the various SubContractors. Fig. 10 demonstrates the links created between the concept construction Materials and the properties of those materials. Analysis of the construction ontology in this development stage shows following statistics: • 105 concepts, • 39 object properties and • 5 data properties.
Fig. 9. Ontology graph: concept Contract and its relations in the construction ontology
Fig. 10. Ontology graph: concept Material and its relations in the construction ontology
4
Application of the construction ontology into semantic web portal
For the knowledge management that accompanies construction process on the construction site “Underpass Grlava” we used an open source web portal MediaWiki with Semantic MediaWiki extension pack that offers a various add-ons that support semantic technologies. For instance, semantic maps extension provides a service that is capable of displaying construction sites on the map based on coordinates that were semantically annotated somewhere in the text. Next step was integration of the knowledge model, construction ontology, which was created in Protégé, into Semantic MediaWiki. The key of this integration is to transform OWL individuals to article pages, OWL classes to category pages and OWL object or data properties to property pages. Semantic properties link articles in a semantic network and, furthermore, take the plain content to the next level. User (in this case a civil engineer) gets information not only from a specific article but also from the articles that are somehow semantically connected with each other. The Semantic MediaWiki serves as a semantic portal for construction companies (from civil to design and build companies) related to the erection of infrastructure objects on the construction site “Underpass Grlava” (Fig. 11). The construction manager, site foreman and assistant site foreman use the semantic portal as a source of knowledge for daily on-site construction activities.
Fig. 11. Semantic web portal for construction project [10]
On the construction site “Underpass Grlava” six different types of concrete were planned for installation because the construction structure is exposed to permanent moisture due to high groundwater. One such type of concrete is i.e. concrete C25/30 XF2 XD1 where XF2 and XD1 are exposition classes used to describe chemical and physical environmental conditions to which the concrete reinforcement may be subjected. XDn denotes exposure of concrete reinforcement to chlorides (excluding seawater), XFn denotes exposure of concrete reinforcement to frost and thawing salt. It has been realized that the characteristics of the planned concrete are not written in technical documentation available on-site. Construction site management staff admits that it is difficult to remember the abundance of information related to daily site activities. In the construction ontology building materials are semantically related to structural elements (Fig. 12).
Fig. 12. Semantic web portal for construction project: material is semantically linked to the construction
With the use of semantic technologies, which are available on construction site in the form of a semantic web portal (or knowledge portal) we can improve the quality of the construction project. The quality is improved directly (i.e. smart and semantically integrated access to explicitly written construction project information) and indirectly (better quality tacit-to-tacit knowledge exchange between site staff).
5
Conclusion
In the paper we have analysed requirements for knowledge management in the AEC industry (Architecture, Engineering, Architecture) from the notion of interrupted information flow in the lifecycle of a construction object (i.e. building or infrastructure object). The purpose of the development of knowledge model for construction projects is its integration into semantic applications. Such application is a semantic web portal, which enables simple, quick and smart access to construction project information. This information can be automatically displayed depending on the semantic links while browsing or through the user’s custom semantic queries. The semantic links facilitate the running of queries. Results of semantic queries are not limited to text only format (i.e. query returns list of material for construction object), but can
also return semantically generated maps (i.e. locations of construction site objects on a map) that leads to further semantically information mining. The knowledge model results in better management of knowledge and facilitates intermediation on a construction project, where the ontology is used to facilitate knowledge sharing and reuse among all personnel involved in the construction project. This cognitive process allows for the streamlining of cross functional decision making at all levels of project delivery. The semantic web portal is a vast repository of construction project information where the project can be described to a level of granularity as desired by the design team, which greatly facilitates knowledge transfer and sharing within a construction team. Our future research will also seek for supporting ideas in the Internet of Things (IoT) domain. This is because IoT also depends on semantic modelling, which provides a potential basis for interoperability among different systems and applications [14]. In the construction industry IoT directs research towards automated processes during design, engineering, erection and maintenance of a construction.
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