Smart Asset Management in the construction sector
– A holistic research into utilising the potential of sensor technology
– An in-depth analysis of the application of Smart Asset and Smart Asset Network
P5 presentation 16th of December, 11:00 at BK-CZ T
1st Wilko Quak (OTB)
2nd Sander van Nederveen (CiTG)
3rd Marcel Hertogh (Professor @ CiTG)
4th Martinus van de Ruitenbeek (Volker InfraDesign)
Delegate: Gerdy Verschuure-Stuip (Assistant Professor @ Architecture)
The introduction of integrated contracts in the construction sector results in shifting risks and responsibilities from the client to the contractor. In contrast to traditional forms of contracting, contractors become often also responsible for an operational period. The obligation to ensure availability and reliability of infrastructural assets to the client demands Dutch contractors to create smart and innovative solutions for Asset Management (AM). Meanwhile, recent developments such as Smart Cities and Internet of Things (IoT) result in an increase in the application of sensor devices from 16 billion in 2014 to 40.9 billion forecasted in 2020. The use of smart sensor technology to detect and predict the performance of assets during the maintenance phase of road infrastructure projects is still in its development phase. The application of sensors to establish an asset network offers a great potential to the construction sector.
This Double Degree graduation work is a combination of two master studies from the Technical University of Delft: Construction Management and Engineering (CME) and Geomatics for the Built Environment. Although the entire research consists of two separate theses, each thesis includes an integrated approach from both studies. The partition of the research in two theses allows a holistic research into the potential of sensor technology for the construction sector and an in-depth analysis of the application of sensors. This holistic research answers the following research question: How can the construction sector incorporate sensor technology during the maintenance phase of road infrastructure projects to optimise Asset Management?
The developed theoretical framework presents three subjects: the individual asset, the asset network and AM. The research explains the potential of sensor technology by elaborating on the overlap between these three subjects. This resulted in the author’s definition of Smart Asset Management (SAM). SAM is the collection, analysis, sharing and exploitation of sensor data to balance performance, costs and risks by performing the right maintenance at the right time and at the right location.
SAM is a combination of an individual Smart Asset (SA) and a collection of SA in a Smart Asset Network (SAN). An individual SA allows to collect and analyse data of attached sensors. A SAN shares and exploits relevant sensor data between assets mutually. This network allows indicating the performance of each asset, regardless of the number of attached sensors.
The analysis of the current situation indicates the connection between Smart Cities and sensors through performance, information and data requirements. In addition, three case studies have been analysed: (1) Project structures and embankments monitoring Haarlem, (2) Project real-time railway monitoring Zeeland, and (3) Project van Brienenoord-bridge Rotterdam. The multiple case study analysis reveals that the content of the set requirements influences the applied management style for AM, which in turn determines the incorporation of sensor technology. The research at hand therefore distinguishes 15 requirements for realising SAM, of which providing insight into the aspects availability and reliability of assets are the most important. The requirements contribute to four set objectives: 1) to store and retrieve performance data in order to improve insight in the actual and real-time condition of assets, 2) to predict future conditions and service levels, 3) to support efficient planning of maintenance activities, and 4) to integrate new technologies and to innovate. The developed theoretical implementation describes how the SA and SAN contribute to the scenario of ‘Asset Manager of the future’.
The theory of SAM has been tested in the research of Braaksma (2016). The results of the testing were evaluated and 12 out of 15 requirements were satisfied. The combination of SA and SAN seems to be a suitable combination for realising a SAM application in the construction sector. It allows sharing sensor data when needed, and thereby utilizing the data for multiple applications. However, three requirements were not fully satisfied due to limitations in and their relevance for this test set-up: (1) defining the exact performance pattern, (2) providing the reliability factors of detected performances, and (3) data security and privacy. The requirements remain important in realising SAM, though were not of crucial importance in this research. The extension of the test set-up in a prototype is likely to resolve these requirements.
In conclusion, implementing the ‘Asset Manager of the future’ scenario answers the research question by posing SAM as a way to optimise AM: it improves insight into asset performance and supports improved decision-making by Asset Managers. It aims to support the construction sector in the obtained responsibility to ensure availability and reliability of assets. This research attempted to show the theoretical potential of sensor technology in the maintenance phase and evaluated requirements for implementing SAM theoretically. To create a completely automated process for collecting, analysing, sharing and exploitation of sensor data in the construction sector, it is recommended to translate this theoretical implementation into an operational practice. Explicitly focusing on innovation, acknowledging the importance of users in the process and realising a pilot project are focal points for research in the near future. This research shows that SAM provides the construction sector with a smart and innovative solution for AM, utilizing the potential of sensor technology to perform the right maintenance at the right time and at the right location.