Annual Conference of the Prognostics and Health Management Society, 2010
A Design for Availability Approach for Use with PHM
Taoufik Jazouli
Peter Sandborn
Center for Advanced Life Cycle Engineering (CALCE)
Department of Mechanical Engineering
University of Maryland
College Park, MD 20742
Abstract:
Prognostics and Health Management (PHM)
methods are incorporated into systems for the
purpose of avoiding unanticipated failures that
can impact system safety, result in additional
life cycle cost, and/or adversely affect the
availability of the system. Availability is the
probability that a system will be able to
function when called upon to do so.
Availability depends on the system's
reliability (how often it fails) and its
maintainability (how efficiently and frequently
it is pro-actively maintained, and how quickly
it can be repaired and restored to operation
when it does fail). Availability is directly
impacted by the success of PHM.
Increasingly, customers of critical systems are
entering into availability contracts in which
the customer either buys the availability of the
system (rather than actually purchasing the
system itself) or the amount that the system
developer/manufacturer/supplier is paid for
the system is a function of the availability
achieved by the customer. Predicting
availability based on known or predicted
system reliability, operational parameters,
logistics, etc., is relatively straightforward and
can be accomplished using existing methods.
However, while determining the availability
that results from a set of events is
straightforward, determining the events that
result in a desired availability is not, and
prediction of a systems attributes to meet an
availability requirement can only be
accomplished using brute force search-based
methods that are not general and become
quickly impractical for real systems and when
uncertainties are introduced. This paper
presents a design for availability approach
that starts with an availability requirement and
uses it to predict the required logistics, design
and operation parameters. The method is
general and can be applied when the inputs to
the problem are uncertain (even the
availability requirement can be a probability
distribution). The method is demonstrated on
several examples with and without PHM.