Value of structural health information in partially observable stochastic environments

TL;DR

This paper develops theoretical and computational methods to quantify the value of structural health information in decision-making for deteriorating systems modeled as POMDPs, improving long-term safety and cost efficiency.

Contribution

It introduces and analyzes VoI and VoSHM metrics within POMDP frameworks, linking them to optimal policies and providing computational solutions for complex deteriorating environments.

Findings

POMDP policies inherently utilize VoI for optimal observational decisions

SHM and inspection information improve long-term policy costs

Point-based value iteration effectively solves POMDPs in structural health management

Abstract

Efficient integration of uncertain observations with decision-making optimization is key for prescribing informed intervention actions, able to preserve structural safety of deteriorating engineering systems. To this end, it is necessary that scheduling of inspection and monitoring strategies be objectively performed on the basis of their expected value-based gains that, among others, reflect quantitative metrics such as the Value of Information (VoI) and the Value of Structural Health Monitoring (VoSHM). In this work, we introduce and study the theoretical and computational foundations of the above metrics within the context of Partially Observable Markov Decision Processes (POMDPs), thus alluding to a broad class of decision-making problems of partially observable stochastic deteriorating environments that can be modeled as POMDPs. Step-wise and life-cycle VoI and VoSHM definitions are devised and their bounds are analyzed as per the properties stemming from the Bellman equation and the resulting optimal value function. It is shown that a POMDP policy inherently leverages the notion of VoI to guide observational actions in an optimal way at every decision step, and that the permanent or intermittent information provided by SHM or inspection visits, respectively, can only improve the cost of this policy in the long-term, something that is not necessarily true under locally optimal policies, typically adopted in decision-making of structures and infrastructure. POMDP solutions are derived based on point-based value iteration methods, and the various definitions are quantified in stationary and non-stationary deteriorating environments, with both infinite and finite planning horizons, featuring single- or multi-component engineering systems.