Abstract

International audience; Humans are and will remain one of the critical constituents of a technological system. The study of Human Factors is a broad domain with equally varying applications. Quantification thereof, with a Human Reliability Analysis (HRA) poses considerable challenges and advantages. In increasingly complex modern systems where large resources are allocated towards ensuring system's operational safety, it becomes necessary to analyze the actions of human operator who directly or indirectly influences system reliability. This paper envisages establishing a base towards a HRA model, to address existing issues. Railway systems and Advanced Driver Assistance Systems for automobiles are our application domains; we aim to identify the need of and usability in both. Human considered as a component of the System of Systems for risk assessment allows us to study its impact on system reliability and give feedback to improve system safety.

Abstract

In recent years, more and more manufacturers and operators of fleets of mobile systems have been focusing their efforts on studying and developing conditional maintenance, monitoring, and diagnostic strategies to cope with an increasingly competitive, unstable, costly, and unpredictable environment. This paper proposes a case study concerning the application of a novel event management architecture, called EMH2, to a fleet of trains. This EMH2 architecture, which applies the holonic paradigm, aims to facilitate the monitoring and diagnosis of a fleet of mobile systems. It is based on a recursive decomposition of cooperative monitoring holons. The definition of a generic event modeling, called SurfEvent, is the second key element of the contribution. EMH2 has been designed to be applicable to any kind of system or equipment up to fleet level. The edge computing paradigm has been adopted for implementation purpose. The EMH2 architecture is designed to facilitate asynchronous and progressive onboard and off-board deployments. A real-world application of EMH2 to a fleet of ten trains currently in use, in collaboration with our industrial partner, Bombardier Transport, is presented. Three key performances indicators have been estimated by comparing EMH2 with the current industrial situation. These indicators are (1) the number of fleet maintenance visits, (2) the time needed by a maintenance operator to investigate and diagnose, and (3) the time needed by the system to update data regarding the health status and monitoring of trains. Results obtained outperformed industrial expectations. The paper finally discusses feedbacks from experience and limitations of the work. Document type: Article