1,721,230 research outputs found
Prescriptive block replacement policy for production degrading systems
No full textMost of the current research in production management is related to the question of integrating data analytics in optimization models. This leads to some very nice models, especially for maintenance planning. Nevertheless, from our point of view, the question of integrating such data-based maintenance optimization models in production planning context remains challenging. The objective of this work is to investigate first insights into prescriptive maintenance within production management context. In this paper, we propose to elaborate a maintenance decision model for a degrading production system. The model allows to optimize both the expected capacity for production planning without maintenance interruption and a condition preventive replacement setting out of the production time. The maintenance decision is also extended to ensure the production objectives with a new prescriptive decision: the acceleration or deceleration production rate which also impacts the degradation speed
Misspecification Analysis of a Gamma- with an Inverse Gaussian-Based Degradation Model in the presence of Measurement Error
No full textGamma- and inverse Gaussian-based degradation models are natural choices for modelling monotonic degradation phenomena. Although not equivalent, in many applications these models are treated to each other. This situation makes the model misspecification problem interesting and important, especially when data are affected by measurement error, because from this kind of data it is not possible to check whether the selected model is able to fit the hidden degradation process or not. Motivated by the above considerations, in the paper we have carried out a small (i.e., very preliminary) Monte Carlo study to evaluate the effect produced by a misspecification of a gammawith an inverse Gaussian-based perturbed degradation process. The study is performed considering as reference model a perturbed Gamma process recently proposed in the literature. The competing model is new and has been constructed with the aim of facilitating the misspecification study. In fact, it is an inverse Gaussian-based perturbed degradation model that share the same parameters and the same error term of the reference model. By virtue of the adopted setup, the mean and variance functions of the considered hidden Inverse Gaussian and Gamma processes
have identical functional forms. The measurement error is modelled by a 3-parameter inverse gamma random variable, which depends in stochastic sense on the hidden degradation level. Model parameters are estimated by adopting the maximum likelihood method, via a sequential Monte Carlo approach. The fitting ability of the considered competing models is evaluated by using the Akaike information criterion. The effect of the misspecification is highlighted on the maximum likelihood estimate of mean remaining useful life. The impact of the presence of measurement error on the severity of the misspecification problem is also evaluated by comparing the obtained results with those attained by performing the same misspecification analysis in the absence of measurement error
A Prescriptive Maintenance Policy for a Gamma Deteriorating Unit
No full textMost of the recent research in the field of maintenance is focused on using more and more information about the state of the system and its environment for predicting future events and making prescriptions about maintenance and operations. Indeed, these prescriptions take the form of recommendations that do not only describe what, how, and when to conduct the maintenance but also consist in advice on how to adjust the system operating conditions for the desired outcome. By following this general idea, this paper suggests a new maintenance policy for a degrading unit that generalizes a policy recently proposed in the literature by including the possibility of influencing the remaining useful life of the unit by changing its usage rate. In fact, this policy assumes that an inspection is performed at a prefixed time and that, based on the result of the inspection, it is decided whether to immediately replace the unit or to postpone its replacement to a second predetermined time and possibly adjust its working rate, if this latter option is deemed convenient. After each replacement the unit is considered as good as new. The degradation process of the unit is described by using a gamma process based model. The unit is assumed to fail when its degradation level passes an assigned threshold. It is supposed that failures are not self-announcing and that failed units can continue to operate, though with reduced performance and/or additional costs. Maintenance costs are computed considering the cost of a preventive replacements, corrective replacements, inspections costs, logistic costs, downtime costs (which account for time spent in a failed state), and costs that account for the change of the unit working rate. This latter cost also includes the possible penalty determined by failure to comply with contract clauses. The optimal maintenance policy is defined by minimizing the long-run average reward rate
An Adaptive Hybrid Maintenance Policy for a Gamma Deteriorating Unit in The Presence of Random Effect
No full textIn this paper, we propose an adaptive hybrid age/condition-based maintenance policy for units whose degradation paths can be modelled via a gamma process with random effect. The maintenance policy consists in measuring the degradation level of the unit at a first (age-based) inspection time, and in using a condition-based rule to decide whether to immediately replace the unit or to postpone its replacement to a future time that is determined, unit by unit, based on the outcome of the inspection. The optimal maintenance policy is defined by minimizing the long-run average cost rate. After each replacement the unit is considered as good as new. The lifetime of the unit is defined by using a failure threshold model. Maintenance costs are computed accounting for preventive replacement
cost, corrective replacement cost, inspection cost, logistic cost, and downtime cost (which depends on the time spent in a failed state)
A Hybrid Maintenance Policy for a Deteriorating Unit in the Presence of Three Forms of Variability
No full textIn this paper, a hybrid condition-/age-based maintenance policy is proposed for deteriorating units whose observed degradation paths are affected by temporal variability, unit to unit variability, and measurement error. The hidden degradation process is described by using a gamma model with random effect. The measurement error is modeled as a non-Gaussian random variable. Units are assumed to fail when their degradation level exceeds a given threshold. The suggested maintenance policy consists in using the information obtained at a predetermined inspection time to decide whether to immediately replace the unit or to postpone its replacement to a successive predetermined time. The inspection involves measuring the degradation level of the unit. It is supposed that an imperfect procedure is firstly adopted, which provides a perturbed measurement of the true degradation level. However, it is also supposed that a more expensive perfect measurement procedure can be optionally used, depending on the result provided by the imperfect one. The proposed maintenance policy is applied to a real-world inspired case of a pipeline. The performances of the policy are measured in terms of the long-run average maintenance cost rate. Obtained results demonstrate the affordability and utility of the proposed approach
Remaining useful life estimation of gamma degrading units characterized by a bathtub-shaped degradation rate in the presence of random effect and measurement error
No full textThis paper proposes a new non-homogeneous gamma process with bathtub-shaped degradation rate function that can be used in the presence of random effect and measurement error. The proposed model is not mathematically tractable. Its main features are illustrated. The probability distribution function of the remaining useful life is formulated by using a failure threshold model. The maximum likelihood estimation of the parameters of the model from perturbed data is addressed. A procedure that combines expectation-maximization algorithm and particle filter method is suggested that allows to significantly mitigate the numerical problems posed by the direct maximization of the likelihood function. The same particle filter algorithm is also adopted to compute the probability distribution function of the remaining useful life, which constitutes the core prognostic tool in condition-based maintenance. As a motivating example, the proposed model is applied to a set of real degradation data of metal oxide semiconductor field-effect transistors. Obtained results demonstrate the utility of the proposed model and the affordability of the suggested estimation procedure
Characterization of Long-period Ship Wave Loading and Vessel Speed for Risk Assessment for Rock Groyne Designs via Extreme Value Analysis
No full textDuring the last two decades, increasing vessel size in major German estuaries has led to the significant change of the local loading regime i.e. increased importance of ship-induced waves and currents. As a consequence, the intensity of ship-induced loads has increased considerably, resulting in damage to rock structures such as revetments, training walls, and groynes. Research into the causes of rock structure deterioration by the Federal Waterways Engineering and Research Institute (BAW) has shown that for large ships in relatively narrow waterways, the long-period primary ship wave loading has become the most prescient factor for rock structure damage. Looking into the future, it can be expected that the increase in the vessel dimensions will lead to an increase in the ship-wave loading. For this reason, analysing long-term changing trends of long-period ship waves and vessel speed to understand the wave-structure interaction is of significant importance. In this study, the stochastic characterization of long-period primary wave height, drawdown, and speed of the vessel through the water at Juelssand in the Lower Elbe Estuary was analysed via extreme value analysis and copula modeling, and the bivariate return periods were calculated. The one-parameter bivariate copula was utilized to analyse the data. The dependence pattern between the variables was investigated using five parametric copula families: Gaussian, Gumbel, Clayton, Frank, and student's t.Accepted Author ManuscriptHydraulic Structures and Flood Ris
A Perturbed Gamma Process with Random Effect and State-Dependent Error
No full textIn this paper, a new perturbed gamma degradation process where the measurement error depends in stochastic sense on the hidden degradation level. This new model generalizes a perturbed gamma process recently suggested in the literature, by allowing for the presence of a unit-specific random effect. The main features of the proposed model are highlighted. Model parameters are estimated, from the available perturbed measurements, by means of the maximum likelihood method. The conditional probability density functions of both the actual and the measured degradation levels, given the past noisy measurements, are computed by using a particle filtering method. Finally, a numerical application is developed on the basis of a set of real degradation data gathered via periodic inspections, where it is discussed the effect of neglecting the presence of random effect on the estimates of the cumulative distribution function of the remaining useful life of the considered degrading units. Obtained results demonstrate the affordability and prove the usefulness and effectiveness of the proposed generalization
Predictive Aircraft Maintenance: Modeling and Analysis Using Stochastic Petri Nets
No full textPredictive aircraft maintenance is a complex process, which requires the modeling of the stochastic degradation of aircraft systems, as well as the dynamic interactions between the stakeholders involved. In this paper, we show that the stochastically and dynamically colored Petri nets (SDCPNs) are able to formalize the predictive aircraft maintenance process. We model the aircraft maintenance stakeholders and their interactions using local SDCPNs. The degradation of the aircraft systems is also modeled using local SDCPNs where tokens change their colors according to a stochastic process. These SDCPN models are integrated into a unifying SDCPN model of the entire aircraft maintenance process. We illustrate our approach for the maintenance of multi-component systems with k-out-of-n redundancy. Using SDCPNs and Monte Carlo simulation, we analyze the number of maintenance tasks and potential degradation incidents that the system is expected to undergo when using a remaining useful life(RUL)-based predictive maintenance strategy. We compare the performance of this predictive maintenance strategy against other maintenance strategies that rely on fixed-interval inspection tasks to schedule component replacements. The results show that by conducting RUL-based predictive maintenance, the number of unscheduled maintenance tasks and degradation incidents is significantly reduced.Accepted Author ManuscriptAir Transport & Operation
Bayesian Networks for Estimating Hydrodynamic Forces on a Submerged Floating Tunnel
No full textA submerged floating tunnel (SFT) is a novel structure that allows crossing waterways where immersed tunnels or bridges are not viable. However, no SFT has been built yet mainly, due to lack of experience. In consequence, there are several uncertainties regarding its design and construction. An effect that should be further investigated is the structural response of the SFT under the simultaneous action of waves and currents. For this purpose, extreme values of waves and currents that were generated through a vine-copula model are used as input in a statistical model based on Bayesian Networks (BNs). The BNs are used to study the conditional correlation (i.e the correlation between random variables conditionalized on a given event) between the hydrodynamic forces acting on the SFT and metocean variables such as waves and currents. This methodology was applied to a case study in China for a SFT aimed to be built at the Qiongzhou Strait. Moreover, the BN model was used to test twelve different configurations of the SFT, with varying submergence depths and diameter sizes. The proposed methodology can be used to provide a more realistic estimation of the forces on the SFT by considering the dependence between the variables of interest. Moreover, this methodology can be extended to test different configurations of the SFT and other hydraulic or maritime structures subjected to simultaneous loading.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Hydraulic Structures and Flood Ris
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