Value of information in sequential decision making: Component inspection, permanent monitoring and system-level scheduling

Memarzadeh, Milad; Pozzi, Matteo

doi:10.1016/j.ress.2016.05.014

Cited by 77 publications

(54 citation statements)

References 30 publications

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“…We plot the relation VoI versus P DAM in log‐scale, despite this can mask piecewise linearity of this relation. Graphs similar to Figure f are also reported by Memarzadeh and Pozzi, for a different setting.…”

Section: Parametric Investigationsupporting

confidence: 82%

“…Cost C r is incurred once the component is repaired, and the agent has to pay cost C f in case of its failure. Moreover, following the assumption in Memarzadeh and Pozzi, no lack of functioning or cost derives from the appearance of the damage: Only the failure induces a direct economic loss. Costs are assumed to be discounted using factor γ 1 per unit time…”

Section: Continuous and Discrete Modeling Of The Maintenance Processmentioning

confidence: 96%

“…To include its contribution, we define the expected cost U ∗ as

U^{*} false(b_{0} false) = true \sum_{h_{0} = 1}^{| H | + 1} P false(h_{0} false| b_{0} false) V_{w}^{*} false(b_{0} false),

where

P false(h_{0} false| b_{0} false) = \sum_{s = 1}^{false| S false|} E_{P} false(s, h_{0} false) b_{0} false(s false)

. This is the so‐called stochastic allocation (SA) model, proposed by Memarzadeh and Pozzi . The VoI analysis can be obtained by comparing the results of the cost analysis with and without the monitoring system as

V o I = V_{w false/ o}^{*} - U^{*} .

…”

Section: Voi In Pomdpsmentioning

confidence: 99%

“…To introduce our analysis, we define a basic parameter setting for the O&M process of a deteriorating component. We have derived the parameters from the deterioration process of a wind turbine component . Time is discretized in years, so δt = 1 year.…”

Section: Parametric Investigationmentioning

confidence: 99%

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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: Parametric Investigationsupporting

confidence: 82%

Section: Continuous and Discrete Modeling Of The Maintenance Processmentioning

confidence: 96%

“…To include its contribution, we define the expected cost U ∗ as

U^{*} false(b_{0} false) = true \sum_{h_{0} = 1}^{| H | + 1} P false(h_{0} false| b_{0} false) V_{w}^{*} false(b_{0} false),

where

P false(h_{0} false| b_{0} false) = \sum_{s = 1}^{false| S false|} E_{P} false(s, h_{0} false) b_{0} false(s false)

V o I = V_{w false/ o}^{*} - U^{*} .

…”

Section: Voi In Pomdpsmentioning

confidence: 99%

Section: Parametric Investigationmentioning

confidence: 99%

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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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“…() show how the value of SHM may be quantified for structural systems accounting for the inspection planning. Recent works by Memarzadeh and Pozzi (, b) take basis in the hidden and partially observable Markov decision process modeling. A VoI analysis is performed for systems as an assembly of components accounting for damage, inspection, and repair events and distinguishing perfect and imperfect information in terms of their precision.…”

Section: Introductionmentioning

confidence: 99%

On the Value of Monitoring Information for the Structural Integrity and Risk Management

Thöns

2017

Computer aided Civil Eng

114

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This article introduces an approach and framework for the quantification of the value of structural health monitoring (SHM) in the context of the structural risk and integrity management for systems. The quantification of the value of SHM builds upon the Bayesian decision and utility theory, which facilitates the assessment of the value of information associated with SHM. The principal approach for the quantification of the value of SHM is formulated by modeling the fundamental decision of performing SHM or not in conjunction with their expected utilities. The expected utilities are calculated accounting for the probabilistic performance of a system in conjunction with the associated structural integrity and risk management actions throughout the life cycle, the associated benefits, structural risks, and costs and when performing SHM, the SHM information, their probabilistic outcomes, and costs. The calculation of the expected utilities necessitates a comprehensive and rigorous modeling, which is introduced close to the original formulations and for which analysis characteristics and simplifications are described and derived. The framework provides the basis for the optimization of the structural risk and integrity management based on utility gains including or excluding SHM and inspection information. Studies of fatigue deteriorating structural systems and their characteristics (1) provide decision support for the performance of SHM, (2) explicate the influence of the structural component and system characteristics on the value of SHM, and (3) demonstrate how an integral optimization of SHM and inspection strategies for an efficient structural risk and integrity management can be performed.

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Role of IoT in Industry Predictive Maintenance

Kaliyannan¹,

Anbupalani²,

Kandasamy³

et al. 2023

Integration of Mechanical and Manufacturing Engineering With IoT

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Value of information in sequential decision making: Component inspection, permanent monitoring and system-level scheduling

Cited by 77 publications

References 30 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

On the Value of Monitoring Information for the Structural Integrity and Risk Management

Role of IoT in Industry Predictive Maintenance

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