Niveau : M.A.Sc.

An investigation of the coupling of the physical and digital assets and resources across lifecycle stages in the built environment


The rapid digitalization of the built asset industry is pushing towards a tighter information coupling of physical and digital assets and resources. Such information coupling allows stakeholders to unlock opportunities for considerable gains in terms of performance and value generated through integrated information management. Within the context of Cyber-Physical Systems (CPS) and Digital Twins (DT)s, a growing number of studies are emphasizing on the technical aspects of CPS and DT. However, there still lacks a common definitions, dimensions, characteristics, and concepts pertaining to lifecycle information coupling. Taking full advantage of these concepts requires new constructs, principles, and mechanisms to define and put into relationship various components that comprise the lifecycle information coupling of physical and digital assets and resources. This research project aims to address existing coupling gaps and issues through a taxonomy of Built Asset Lifecycle Information Couples and a Coupling Action Instantiation Framework which provide the dimensions and characteristics framing the physical-digital coupling of assets and resources in the built asset industry. The proposed taxonomy and its instantiation framework contribute to the effort aimed at structuring the knowledge domain of lifecycle information management through the coupling of physical and digital worlds in the built environment.

Résultats du projet

A taxonomy of lifecycle information coupling of built assets and resources was proposed to identify what coupling dimensions and characteristics needed to conceptualize the asset coupling in the built asset industry. The taxonomy offered eight high-level dimensions covering various aspects of information coupling. The proposed dimensions were Information couples, Coupling States, Coupling Outcomes, Coupling Impacts, Coupling Actions, Coupling Metrics, and Coupling Enablers. The dimensions and their characteristics can serve to reduce complexity of asset coupling and allow stakeholders to unlock the value generated through integrated information management. It also supports effective implementation of digital information technologies across the asset’s lifecycle. In order to operationalize and instantiate the key dimensions of the proposed taxonomy, a coupling action instantiation framework was developed as the design product of this research.
The framework was articulated based on the dimensions of the taxonomy and main data categories that underline meaningful data for coupling actions. Moreover, a coupling mechanism was proposed to extract meaningful data from potential information containers and link them to as-targeted and as-built coupling actions. This mechanism functioned as a matrix for integrating data within defined coupling actions to generate various types of Information Couples across lifecycle stages. Evaluation of the proposed taxonomy and its instantiation framework demonstrated that a large volume of dispersed data collected from physical assets can be potentially harmonized and coupled with their digital assets at different information states. Systematic organization of such data and coupling them with physical assets can improve the collaboration between parties and allow stakeholders to make more informed decisions about actual condition of the asset.

Contributions du projet

In response to ongoing trends towards digital twinning of physical and digital built assets, the proposed artifact did not aim to replace any given taxonomy in the context of CPS. Instead, it extended and framed existing concepts and theories into practice while addressing current asset coupling issues in the built asset industry. Using the characteristics of the taxonomy can help decision makers to identify what data needs to be coupled form the early stages of a project. This results in better management of information, reduction of time and cost during construction process, and effective extraction of data from as-built assets for reusability or recycling purposes. Indeed, automation of systems highly relies on taxonomies. Without taxonomies, it would be difficult to identify what would be required for automation purposes.


Les publications de ce projet sont disponibles ci-dessous :


L’équipe chargée de ce projet

Érik Poirier


Ce projet a été supporté par :

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