Early in the design process, informed decisions must be made to ensure that the developed system will be resilient—that is, capable of preventing, mitigating, or recovering failures. However, at this phase of design, many options exist to achieve resilience, each with different effects on the system’s fault response, performance, and difficulty to implement. As a result, it is important to be able to quantify the value of a design’s resilience so that it can be traded off against these other concerns. Advancements in the capabilities of Prognostics and Health Management, fault-tolerant control and related technologies have enabled a variety of novel prevention and recovery features that require an understanding of the system’s structure and available functions during operation to consider properly. This work aims to develop modelling and design frameworks enabling the consideration of these features, such as system reconfiguration, functional redundancy, operational failure avoidance, and goal change early in the design process. Such design frameworks will show which designed features are most appropriate in the system and will account for the uncertainty of assumptions made in early design phase.
How to Cite
This work is licensed under a Creative Commons Attribution 3.0 Unported License.
The Prognostic and Health Management Society advocates open-access to scientific data and uses a Creative Commons license for publishing and distributing any papers. A Creative Commons license does not relinquish the author’s copyright; rather it allows them to share some of their rights with any member of the public under certain conditions whilst enjoying full legal protection. By submitting an article to the International Conference of the Prognostics and Health Management Society, the authors agree to be bound by the associated terms and conditions including the following:
As the author, you retain the copyright to your Work. By submitting your Work, you are granting anybody the right to copy, distribute and transmit your Work and to adapt your Work with proper attribution under the terms of the Creative Commons Attribution 3.0 United States license. You assign rights to the Prognostics and Health Management Society to publish and disseminate your Work through electronic and print media if it is accepted for publication. A license note citing the Creative Commons Attribution 3.0 United States License as shown below needs to be placed in the footnote on the first page of the article.
First Author et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 United States License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.