All Outputs (4)

A methodology for railway track maintenance modelling using Plausible Petri nets (2018)
Presentation / Conference
Chiachio, M., Chiachio, J., Prescott, D., & Andrews, J. (2018, September). A methodology for railway track maintenance modelling using Plausible Petri nets. Paper presented at Probabilistic Safety Assessment and Management PSAM 14

This paper proposes a new mathematical methodology to model expert systems with the ability to sequentially learn from data. To this end, the Plausible Petri nets (PPNs) methodology, first developed in M. Chiachío et al. [Proceedings of the Future Te... Read More about A methodology for railway track maintenance modelling using Plausible Petri nets.

Modelling adaptive systems using plausible Petri nets (2018)
Conference Proceeding
Chiachío, J., Chiachío, M., Prescott, D., & Andrews, J. (2018). Modelling adaptive systems using plausible Petri nets. In 8th International Workshop on Reliable Engineering Computing, “ Computing with Confidence ”

One of the main challenges when analyzing and modelling complex systems using Petri nets is to deal with uncertain information, and moreover, to be able to use such uncertainty to dynamically adapt the modelled system to uncertain (changing) contextu... Read More about Modelling adaptive systems using plausible Petri nets.

A knowledge-based prognostics framework for railway track geometry degradation (2018)
Journal Article
Chiachío, J., Chiachío, M., Prescott, D., & Andrews, J. (2019). A knowledge-based prognostics framework for railway track geometry degradation. Reliability Engineering and System Safety, 181, 127-141. https://doi.org/10.1016/j.ress.2018.07.004

This paper proposes a paradigm shift to the problem of infrastructure asset management modelling by focusing towards forecasting the future condition of the assets instead of using empirical modelling approaches based on historical data. The proposed... Read More about A knowledge-based prognostics framework for railway track geometry degradation.

A Bayesian assessment for railway track geometry degradation prognostics (2018)
Conference Proceeding
Chiachío, J., Chiachío, M., Prescott, D., & Andrews, J. (2018). A Bayesian assessment for railway track geometry degradation prognostics. In Proceedings of the 4th European Conference of the Prognostics and Health Management Society

Advanced PHM techniques have the potential to substantially reduce railway track maintenance costs while increasing safety and availability. However, there is still a significant lack of knowledge and experience in relation to suitable PHM models and... Read More about A Bayesian assessment for railway track geometry degradation prognostics.