Abstract
This paper proposes a model of inspection of a protection system in which the inspection outcome provides imperfect information of the state of the system. The system itself is required to operate on demand typically in emergency situations. The purpose of inspection is to determine the functional state of the system and consequently whether the system requires replacement. The system state is modeled using the delay time concept in which the failed state is preceded by a defective state. Imperfect inspection is quantified by a set of probabilities that relate the system state to the outcome of the inspection. The paper studies the effect of these probabilities on the efficacy of inspection. The analysis indicates that preventive replacement mitigates low-quality inspection and that inspection is cost-effective provided the imperfect inspection probabilities are not too large. Some derivative policies in which replacement is “postponed” following a positive inspection are also studied. An isolation valve in a utility network motivates the modeling.
Highlights
T HIS PAPER studies a protection or preparedness system subject to imperfect inspection
Once a positive inspection has occurred, at kT say, it is supposed that the maintainer decides to postpone replacement for a time τ ; TABLE IV RESULTS FOR REPEATED INSPECTION POLICY
This paper studied imperfect inspection of a protection system
Summary
T HIS PAPER studies a protection or preparedness system subject to imperfect inspection. An isolation valve [10] that is either good or failed may be clearly indicated as such on inspection, but one that is defective may be more difficult to correctly classify as operational This issue arises in medical screening tests, whereby early disease stages are undetectable and the screening error-rate decreases as the disease develops [21]. It is important to study, in an idealized situation (the model), the effect of imperfect inspection upon the efficacy and efficiency of protection systems with a defective state. This can inform maintenance policy and decision making for real systems [22], in order to mitigate the serious consequences of an unmet demand.
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