Thesis

Subject 1 : Semi-automatic formalisation of a knowledge repository supporting the digital twin for building renovation: application to the IsoBIM project

Context:

the ANR ISOBIM project aims to propose a collaborative process for renovation by external ISOlation based on Lean and BIM paradigms. In this context, one of the objectives is to be able to ensure the management of project data in a formal repository capable of covering the design, scheduling, planning and implementation monitoring phases. In addition, this repository will have to support the digital building twin allowing, in particular, 4D simulation in the execution phase of a building site.

Building Information Modelling (BIM) can be defined as « a modeling technology and associated set of processes to produce, communicate and analyse building models » (Sacks, Eastman, Lee, & Teicholz, 2018). Because of its multidisciplinary nature, the construction field brings together different trades and therefore different types of data that need to be grouped together within the same modelling (classic data models, formal knowledge models, such as ontologies, taxonomies, concept hierarchies).

Objectives and issues:

The modelling of information related to the design phase is largely dealt in the BIM. Indeed, beyond the standards commonly used in mechanical design (STEP (Pratt, 2005), IGES (Association & others,1996), DXF (Autodesk, 2010), …), standards have been defined for the modelling of construction data
such as IFC (ISO, 2013) or CIS/2 (Reed, 2003). Within the framework of the IsoBIM project, it is envisaged to integrate 3 business points of view (design, planning and construction monitoring) and their associated constraints to support the renovation process. All of IsoBIM’s activities require an
adequate information system implementing various functionalities, including efficient clustering algorithms, a data model capable of storing multimodal data: geometric (panels from the layout possibilities), planning (resources, stocks, ranges, etc.) and site monitoring (task status, estimatedtime, person in charge of the task, etc.). This information system could be used to support the digital twin of the renovation process.

We are therefore interested in the following research questions:

1. Which data structure would be the most suitable for our digital twin?
2. How can this structure be obtained automatically to reduce the modelling time/difficulty?

To answer these two questions, this work will seek to explore the use of data mining tools to propose the following contributions:

• A formalization of knowledge in ontological form to structure the concepts of the digital twin of the renovation process.
• A semi-automatic methodology to obtain this formalisation, based on clustering algorithms.

This last point will be based on data mining, with two methods already envisaged. Firstly, the Formal Concept Analysis (FCA) method (Ganter, Stumme, & Wille, 2004) would be used for knowledge modelling based on a set of examples or structured data. In a second step, its extension Relational Concept Analysis (RCA) (Rouane-Hacene, Huchard, Napoli, & Valtchev, 2013) (Wajnberg, Valtchev, Lezoche, Panetto, Blondin Massé, 2019) would be used for the extraction of relationships between each knowledge domain.

Candidate profile:

• Student with a master’s degree in computer science or industrial engineering,
• Knowledge in data and knowledge modelling.
• Ability to work in a team

Location of the thesis:

The thesis will take place at the CRAN-Epinal

Salary:

~ 1768.55 brut (1400€ net)

Planned start-up:

September 2021

Contacts :

Bibliography :

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• Ganter, B., Stumme, G., & Wille, R. (2004). Formal Concept Analysis: Theory and applications-J. UCS Special Issue. Journal of Universal
  Computer Science, 10(8), 926.
• ISO. (2013). Industry Foundation Classes (IFC) for data sharing in the construction and facility management industries. Consulté à l’adresse
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