Title: Dependability of Sensor Networks for Industrial Prognostics and Health Management,
Abstract: Maintenance is an important activity in industry. It is performed either to
revive a machine/component or to prevent it from breaking down. Different
strategies have evolved through time, bringing maintenance to its current
state: condition-based and predictive maintenances. This evolution was due to
the increasing demand of reliability in industry. The key process of
condition-based and predictive maintenances is prognostics and health
management, and it is a tool to predict the remaining useful life of
engineering assets. Nowadays, plants are required to avoid shutdowns while
offering safety and reliability. Nevertheless, planning a maintenance activity
requires accurate information about the system/component health state. Such
information is usually gathered by means of independent sensor nodes. In this
study, we consider the case where the nodes are interconnected and form a
wireless sensor network. As far as we know, no research work has considered
such a case of study for prognostics. Regarding the importance of data
accuracy, a good prognostics requires reliable sources of information. This is
why, in this paper, we will first discuss the dependability of wireless sensor
networks, and then present a state of the art in prognostic and health
management activities.