Model-based quality assurance in railway infrastructure planning

Häußler, Marco; Borrmann, André

doi:10.1016/j.autcon.2019.102971

Cited by 19 publications

(20 citation statements)

References 33 publications

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“…Regarding checking processes, the distinction between data and geometric checking is well marked but there are few works which attempt to fix semantic-geometric coherence of models [14,15]. The identification of this issue is of great importance to accurately deliver high quality models, and it is where BIM offers real opportunities, when it enables to detect implicit knowledge as a domain expert would [16].…”

Section: Discussionmentioning

confidence: 99%

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An Approach for Data Extraction, Validation and Correction Using Geometrical Algorithms and Model View Definitions on Building Models

Luttun¹,

Krijnen

2020

Lecture Notes in Civil Engineering

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The Industry Foundation Classes (IFC) cover a wide variety of subdomains in the construction industry. Model View Definitions (MVD) enable to specify a subset of the IFC schema to assess the content of a model for specific use cases and information exchanges.However, IFC and MVD paradoxically complexify the workflow since it requires a deep understanding of the schema combined with construction knowledge to carry out simple use cases such as quantity checking or data export. This gap between domain specific queries and their expression in a computerreadable language weakens the opportunities provided to the building industry by Building Information Modeling.Our research consists in the implementation of MVDs in a high-level programming language to extract data from building models, an assessment of the extraction results and geometrical processing algorithms to correct the explicit quantities and properties that are supplied as metadata alongside the elements in IFC building models.Geometrical processing can be used to reduce and eventually correct errors on property values. We use a generic geometrical representation of IFC entity instances and apply geometrical transformations on those to obtain geometrical shapes. Boolean operations are used to identify relationships between elements. Eventually, incorrect data values are corrected directly in the IFC models accordingly to the IFC schema.For instance, we authored an MVD to extract data pertaining to external walls from different IFC models and corrected the value of the IsExternal property of the models' IfcWall entities. This use case is of great importance for the cost estimation of a thermal renovation on a building as it gives a good estimate of the outer surface area of the building envelope.

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Section: Discussionmentioning

confidence: 99%

“…There is still a vast majority of models containing lacking, unverified, wrong, or misleading information. A model that contains errors, or whose data quality has not been checked appropriately, should not represent a trusty basis for real-life checking use cases such as structural analysis or cost estimation [14].…”

Section: 3mentioning

confidence: 99%

An Approach for Data Extraction, Validation and Correction Using Geometrical Algorithms and Model View Definitions on Building Models

Luttun¹,

Krijnen

2020

Lecture Notes in Civil Engineering

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“…This type of model is referred to as an implicit geometry description. With implicit models, the governing design parameters become significantly more accessible than with explicit models' (Häußler and Borrmann, 2020). The description of the design of railway infrastructure in the underlying guidelines is predominantly parameter-oriented (Häußler et al, 2021).…”

Section: Designing In Track Constructionmentioning

confidence: 99%

“…Comparison of implicit and volumetric 3D models: while implicit models (drawing-oriented view) are used during the design process (parametric modeling), explicit models are used in the context of BIM-based analysis (Häußler and Borrmann, 2020).…”

Section: Figmentioning

confidence: 99%

Knowledge-based engineering in the context of railway design by integrating BIM, BPMN, DMN and the methodology for knowledge-based engineering applications (MOKA)

Häußler¹,

Borrmann²

2021

ITcon

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Designing railway infrastructure is a knowledge-intensive task. Although there are a number of mature design authoring systems available, their support for dynamically incorporating domain-specific engineering knowledge is very limited. At the same time, a standardized digital representation of railway engineering knowledge (such as building codes and best practice) does not exists. To overcome this deficiency, this paper proposes the use of Knowledge Based Engineering (KBE) to automate routine design tasks by considering multiple knowledge sources. In this scenario, KBE is used to support a Railway design authoring system. To ensure maximum transparency in the design of the developed KBE application, graphical ‘Business Process Model and Notation’ (BPMN) has been used in combination with ‘Decision Model and Notation’ (DMN) to formalize the underlying engineering knowledge. The KBE application has been developed according to the Methodology for Knowledge-Based Engineering Applications (MOKA). An evaluation of the BPMN/DMN approach shows that it meets up to 58% of the acceptance criteria found in the literature. In addition, BPMN and DMN can already be used in the early capture phase of MOKA and its workflows can be developed into an executable KBE application in the subsequent phases. The results of the test example discussed here show that time savings of up to 97.5% can be achieved in the execution of the KBE application.

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“…BIM focuses on integrating the information of all participants of a project (Santos et al, 2017) to generate an approach to manage the essential data involved in the lifecycle of a project (Wong & Zhou, 2015) as well as changes to processes in it (Cheng et al, 2016). Given its potential to increase efficiency and productivity in the construction industry, BIM has been widely used in construction projects, railway infrastructure, and underground transportation tunnels (Cheng et al, 2016;Lu et al, 2019;Häußler & Borrmann, 2020;Heravi et al, 2019;Hu et al, 2019). However, the relatively low scale of the adoption of BIM, and the fact that it has not been applied in detail, have hindered its maximal use.…”

Section: Introductionmentioning

confidence: 99%

Measuring Value-Added-Oriented Bim Climate in Construction Projects: Dimensions and Indicators

Zhang

Yuan

Xia

et al. 2020

Journal of Civil Engineering and Management

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A value-added-oriented (VAO) BIM climate is the organizational climate of BIM value-added. However, a lack of research on VAO BIM climate has thwarted progress on BIM knowledge systems. By using the socio-technical systems approach and the competing value approach, 12 dimensions and 39 indicators of a VAO BIM climate are proposed and tested using 306 questionnaires collected from workers engaged in BIM construction projects across China. Data was analyzed by confirmatory factor analysis. The results show that the proposed dimensions and indicators are highly reliable and valid. The VAO BIM climate is heavily influenced by autonomy, career development, and task orientation. The top 10 indicators were mainly related to participation, task orientation, and goal effectiveness. And the MWD-BIM, RCS-BIM, CDMT-BIM, and SMD-BIM were mistaken as key indicators of participation, autonomy, peer relations, and organizational adaptability, respectively. The proposed dimensions and indicators can be used to advance scholarly understanding and theory on BIM climate in construction projects through directing resource allocation, enhancing the understanding of human–BIM interactions, improving the BIM knowledge system and facilitating decision framework of BIM adoption. Practical implications for managers in construction projects are provided in the end.

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Model-based quality assurance in railway infrastructure planning

Cited by 19 publications

References 33 publications

An Approach for Data Extraction, Validation and Correction Using Geometrical Algorithms and Model View Definitions on Building Models

An Approach for Data Extraction, Validation and Correction Using Geometrical Algorithms and Model View Definitions on Building Models

Knowledge-based engineering in the context of railway design by integrating BIM, BPMN, DMN and the methodology for knowledge-based engineering applications (MOKA)

Measuring Value-Added-Oriented Bim Climate in Construction Projects: Dimensions and Indicators

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