Inspection, Maintenance, and Repair with Partial Observability

Ellis, Hugh; Jiang, Mingxiang; Corotis, Ross B.

doi:10.1061/(asce)1076-0342(1995)1:2(92)

Cited by 76 publications

(39 citation statements)

References 23 publications

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“…Hence, the degradation process starting from a condition is independent of the past path that took the component to that condition. This is a typical assumption in infrastructure management . If such assumption does not hold true, one needs to define another, more fundamental state, affecting the transitions.…”

Section: Continuous and Discrete Modeling Of The Maintenance Processmentioning

confidence: 99%

What makes long‐term monitoring convenient? A parametric analysis of value of information in infrastructure maintenance

Pozzi

2019

Struct Control Health Monit

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Summary Information collected by monitoring systems can provide a significant economic benefit to the operation and maintenance of infrastructure components only under specific conditions. The information has to be precise, not redundant, related to relevant decision problems under uncertainty as, for example, the appropriate scheduling of maintenance actions, and the decision maker needs to be able to process that information and react timely. All these considerations can be naturally embedded in the value of information (VoI), a utility‐based metric for assessing the impact of the additional information in decision making under uncertainty. In this paper, we investigate the relation between the VoI and key features of the monitoring system, of the component deterioration and of the decision‐making process, including measure accuracy and availability, deterioration rates, damage predictability, reaction time, maintenance costs, and the economic discount factor. By leveraging previous work, we model the maintenance process as a partially observable Markov decision process, and we compute the VoI of long‐term monitoring. Our proposed framework allows for a detailed quantitative analysis on the joint effects of these features and can be useful to identify conditions when the benefit of monitoring is high, to assign priorities among components that deserve to be instrumented or to optimize the allocation of resources to monitoring efforts.

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Section: Continuous and Discrete Modeling Of The Maintenance Processmentioning

confidence: 99%

What makes long‐term monitoring convenient? A parametric analysis of value of information in infrastructure maintenance

Pozzi

2019

Struct Control Health Monit

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“…In an early work, Madanat & Ben-Akiva (1994) adopt POMDPs for decision-making for highway-pavement networks. Ellis et al (1995), and Corotis et al (2005) demonstrate use of POMDPs for bridge inspection planning. Papakonstantinou & Shinozuka (2014a, 2014b provide a thorough overview of solvers suited for solution of large-scale and more realistic problems.…”

Section: Pomdp Implementation In Infrastructure Managementmentioning

confidence: 99%

Observation-based Decision-making for Infrastructure

Chatzi¹,

Παπακωνσταντίνου²,

Hajdin³

et al. 2017

Proceedings of the Joint COST TU1402 - COST TU1406 - IABSE WC1 Workshop: The Value of Structural Health Monitoring for the Reli

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Abstract. The aim of this review paper is to summarize available options for decision-support toward the optimal management of infrastructure systems under consideration of uncertainties. Thereafter, we elaborate on a particular variant, namely Partially Observable Markov Decision Processes (POMDP), as a flexible framework for the incorporation of information from observations (visual inspections, non-destructive testing and monitoring) in the context of optimal inspection and maintenance planning. Examples from the literature are presented, demonstrating the potential of planning under uncertainty and the links to the Value of Information (VoI) from Structural Health Monitoring (SHM).

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“…Industrial usages of the model can be found in mechanical machines whose components are not directly observable (White 1977), or in maintenance inspection of infrastructure systems such as highways and bridges (Ellis et al 1995). Challenging proposals can also be found in systems for independent living.…”

Section: Partially-observed Markov Decision Processmentioning

confidence: 99%

Formal Modeling Techniques for Ambient Assisted Living

Parente¹,

Nugent²,

Hong³

et al. 2010

Ageing Int

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In the development of systems of ambient assisted living (AAL), formalized models and analysis techniques can provide a ground that makes development amenable to a systematic approach. We consider the following formal modeling tools and techniques: fault trees, evidential reasoning, evidential ontology networks, temporal logic, hidden Markov models and partially observable Markov models. We review them in the perspective of their potential in the realm of AAL, recalling the general traits and potential of each of them, and highlighting how this can be concretely deployed within the AAL realm. To this end, we present a number of scenarios providing insight on how each technique can match the needs of different types of problem in the application domain.The present and forecasted evolution of population demographics demands new approaches to the delivery of health and social care (World Health Organization 2010). Technology may largely contribute both to the efficiency and effectiveness of services through solutions that range from assistive technologies such as medication management and cognitive prosthetics to wearable healthmonitoring systems (Paradiso et al. 2005). As a common trait, all these approaches pose a crucial problem pertaining to the automated extraction of high-level semantic information from low-level data acquired through technological devices. This process may take a major role in the profiling of the patient (Atallah and Yang 2009), which in turn provides a basis for supporting decisions needed for effective Ageing Int (2011) 36:192-216

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Inspection, Maintenance, and Repair with Partial Observability

Cited by 76 publications

References 23 publications

What makes long‐term monitoring convenient? A parametric analysis of value of information in infrastructure maintenance

What makes long‐term monitoring convenient? A parametric analysis of value of information in infrastructure maintenance

Observation-based Decision-making for Infrastructure

Formal Modeling Techniques for Ambient Assisted Living

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