The success of an aircraft mission is subject to the fulfillment of some operational requirements before and during each flight. As these requirements depend essentially on the aircraft system components and the mission profile, the effects of failures can be very severe if they are not anticipated. Hence, one should be able to assess the aircraft operational reliability with regard to its missions in order to be able to cope with failures. We address aircraft operational reliability modeling to support maintenance planning during the mission achievement. We develop a modeling approach, based on a meta-model that is used as a basis: (i) to structure the information needed to assess aircraft operational reliability and (ii) to build a stochastic model that can be tuned dynamically, in order to take into account the aircraft system operational state, a mission profile and the maintenance facilities available at the flight stop locations involved in the mission. The aim is to enable operational reliability assessment online. A case study, based on an aircraft subsystem, is considered for illustration using the Stochastic Activity Networks (SANs) formalism.
The overall dependability of an interactive system is one of its weakest components, which is usually its user interface. The presented approach integrates techniques from the dependable computing field and elements of the user-centered design. Risk analysis and fault-tolerance techniques are used in combination with task analysis and modeling to describe and analyze the impact of system faults on human activities and the impact of human deviation or errors on system performance and overall mission performance. A technique for systematic analysis of human errors, effects, and criticality (HEECA) is proposed. It is inspired and adapted from the Failure Mode, Effects, and Criticality Analysis technique. The key points of the approach are: 1) the HEECA technique combining a systematic analysis of the effects of system faults and of human errors; and 2) a task modeling notation to describe and to assess the impact of system faults and human errors on operators' activities and system performance. These key points are illustrated on an example extracted from a case study of the space domain. It demonstrates the feasibility of this approach as well as its benefits in terms of identifying opportunities for redesigning the system, redesigning the operations, and for modifying operators' training.
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