Abstract
The research community generally recognizes the Value of Information (VoI) as a realistic indicator of the benefit of the information provided by a monitoring system in structures management. Even though many authors have recently focused on the assessment of the VoI, most of their works do not consider the presence of two individuals in the decision process of whether to install a monitoring system, the owner and the manager of the structure. In this contribution, we define a framework to quantifying the VoI of a monitoring system by considering these two separate individuals, who have a different aversion toward risk. Moreover, we apply the results on a real-life case study concerning the Streicker Bridge in Princeton, NJ, in the USA. This framework aims to help the owner in quantifying the money saved by entrusting the evaluation of the state of the structure to the monitoring system, even if the manager's behaviour toward risk is different from the owner's own, and so are his or her management decisions. The results of the case study confirm the difference in the two way to quantify the VoI of a monitoring system.
Original language | English |
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Title of host publication | Structural Health Monitoring 2017 |
Subtitle of host publication | Real-Time Material State Awareness and Data-Driven Safety Assurance - Proceedings of the 11th International Workshop on Structural Health Monitoring, IWSHM 2017 |
Place of Publication | Lancaster, Pennsylvania |
Pages | 1324-1331 |
Number of pages | 8 |
Publication status | Published - 21 Dec 2017 |
Event | 11th International Workshop on Structural Health Monitoring 2017: Real-Time Material State Awareness and Data-Driven Safety Assurance, IWSHM 2017 - Stanford, United States Duration: 12 Sept 2017 → 14 Sept 2017 |
Conference
Conference | 11th International Workshop on Structural Health Monitoring 2017: Real-Time Material State Awareness and Data-Driven Safety Assurance, IWSHM 2017 |
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Country/Territory | United States |
City | Stanford |
Period | 12/09/17 → 14/09/17 |
Keywords
- decision support systems
- information management
- managers
- safety engineering
- structural health monitoring