Integrated Inspection Scheduling and Maintenance Planning for Infrastructure Systems

TLDR

Infrastructure operation and maintenance depend on component data, yet limited resources necessitate data collection guided by Value of Information, which is computationally intractable for sequential decisions. This study proposes integrating adaptive maintenance planning via a Partially Observable Markov Decision Process with inspection scheduling based on a tractable VoI approximation. Two myopic approaches—pessimistic and optimistic—are introduced and compared theoretically and through numerical examples.

Abstract

Abstract Operation and maintenance of an infrastructure system rely on information collected on its components, which can provide the decision maker with an accurate assessment of their condition states. However, resources to be invested in data gathering are usually limited and observations should be collected based on their Value of Information (VoI). Assessing the VoI is computationally intractable for most applications involving sequential decisions, such as long‐term infrastructure maintenance. In this article, we propose an approach for integrating adaptive maintenance planning based on Partially Observable Markov Decision Process (POMDP) and inspection scheduling based on a tractable approximation of VoI. Two alternative myopic approaches, namely pessimistic and optimistic, are introduced, and compared theoretically and by numerical examples.