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This paper presents the advantages of using Weibull distributions, within the context of railway signaling systems, for enabling safety-oriented decision-making. Failure rates are used to statistically model the basic event of fault-tree analysis, and their value sizes the maximum allowable latency of failures to fulfill the safety target for which the system has been designed. Relying on field-return failure data, Weibull parameters have been calculated for an existing electronic signaling system and a comparison with existing predictive reliability data, based on exponential distribution, is provided. Results are discussed in order to drive considerations on the respect of quantitative targets and on the impact that a wrong hypothesis might have on the choice of a given architecture. Despite the huge amount of information gathered through the after-sales logbook used to build reliability distribution, several key elements for reliable estimation of failure rate values are still missing. This might affect the uncertainty of reliability parameters and the effort required to collect all the information. We then present how to intervene when operational failure rates present higher values compared to the theoretical approach: increasing the redundancies of the system or performing preventive maintenance tasks. Possible consequences of unjustified adoption of constant failure rate are presented. Some recommendations are also shared in order to build reliability-oriented logbooks and avoid data censoring phenomena by enhancing the functions of the electronic boards composing the system.

A Weibull Approach for Enabling Safety-Oriented Decision-Making for Electronic Railway Signaling Systems