Modélisation de dégradation, modélisation stochastique de phénomène dynamique,
Pronostic et health monitoring (PHM),
Fiabilité,
Maintenance prédictive,
Maintenance conditionnelle
Publications scientifiques au M2P2
2025
Yaxin Shen, Mitra Fouladirad, Antoine Grall. Mathematical modeling of solar farm performance degradation in a dynamic environment for condition-based maintenance. Reliability Engineering and System Safety, 2025, 257, pp.110778. ⟨10.1016/j.ress.2024.110778⟩. ⟨hal-05023346⟩ Plus de détails...
Yaxin Shen, Mitra Fouladirad, Antoine Grall. Mathematical modeling of solar farm performance degradation in a dynamic environment for condition-based maintenance. Reliability Engineering and System Safety, 2025, 257, pp.110778. ⟨10.1016/j.ress.2024.110778⟩. ⟨hal-05023346⟩
Journal: Reliability Engineering and System Safety
Jingqi Zhang, Mitra Fouladirad, Nikolaos Limnios. Sensitivity analysis of an imperfect maintenance policy for Proton-exchange membrane fuel cell based on geometric a semi-Markov model. Reliability Engineering and System Safety, 2025, 255, pp.110674. ⟨10.1016/j.ress.2024.110674⟩. ⟨hal-05023351⟩ Plus de détails...
This paper proposes a maintenance model for a Proton-Exchanged Membrane Fuel Cells system. Two types of failures are considered: non repairable internal failures and possibly repairable external failures. The maintenance involves replacing one or more cells. Therefore the maintenance can be perfect or imperfect. Moreover after each repair, the maintenance operator improves and the down time due to maintenance is reduced. A semi-Markov process is proposed to model the system’s lifetime. In this framework, the reliability measures and the remaining useful lifetime are derived. The long run average maintenance cost is studied. A sensitivity analysis of model parameters and maintenance unit costs is performed and a maintenance optimization strategy is proposed.
Jingqi Zhang, Mitra Fouladirad, Nikolaos Limnios. Sensitivity analysis of an imperfect maintenance policy for Proton-exchange membrane fuel cell based on geometric a semi-Markov model. Reliability Engineering and System Safety, 2025, 255, pp.110674. ⟨10.1016/j.ress.2024.110674⟩. ⟨hal-05023351⟩
Journal: Reliability Engineering and System Safety
Yaxin Shen, Mitra Fouladirad, Antoine Grall. Impact of dust and temperature on photovoltaic panel performance: A model-based approach to determine optimal cleaning frequency. Heliyon, 2024, 10 (16), pp.e35390. ⟨10.1016/j.heliyon.2024.e35390⟩. ⟨hal-05023354⟩ Plus de détails...
Yaxin Shen, Mitra Fouladirad, Antoine Grall. Impact of dust and temperature on photovoltaic panel performance: A model-based approach to determine optimal cleaning frequency. Heliyon, 2024, 10 (16), pp.e35390. ⟨10.1016/j.heliyon.2024.e35390⟩. ⟨hal-05023354⟩
Franck Corset, Mitra Fouladirad, Christian Paroissin. Imperfect and worse than old maintenances for a gamma degradation process. Applied Stochastic Models in Business and Industry, 2024, ENBIS 2022, 40 (3), pp.620-639. ⟨10.1002/asmb.2849⟩. ⟨hal-04462980⟩ Plus de détails...
This article considers a condition‐based maintenance for a system subject to deterioration. The deterioration is modeled by a non‐homogeneous gamma process, more precisely the gamma process and the preventive maintenance are imperfect or worse than old. The corrective maintenance actions are as good as new. The maintenance efficiency or non‐efficiency parameters as well as the deterioration parameters are considered to be unknown. The monitoring data under consideration give indirect information on the maintenance parameters. Therefore, an expected maximum algorithm is applied for parameter estimation.
Franck Corset, Mitra Fouladirad, Christian Paroissin. Imperfect and worse than old maintenances for a gamma degradation process. Applied Stochastic Models in Business and Industry, 2024, ENBIS 2022, 40 (3), pp.620-639. ⟨10.1002/asmb.2849⟩. ⟨hal-04462980⟩
Journal: Applied Stochastic Models in Business and Industry
Arefe Asadi, Mitra Fouladirad, Diego Tomassi. An initial investigation for employing ACH depth function in degradation model selection: A case study with real data. Applied Stochastic Models in Business and Industry, 2024, 40 (3), pp.598-619. ⟨10.1002/asmb.2844⟩. ⟨hal-05023362⟩ Plus de détails...
Abstract In degradation modeling, stochastic processes often do not meet the classical properties necessary for traditional goodness‐of‐fit tests. This paper presents an initial investigation into employing the ACH depth function and its potential in degradation model selection. We commence by presenting various stochastic processes as degradation models and their selection criteria. Subsequently, we delve into the ACH depth function, highlighting its potential in this context. Through simulated data, we assess the application of this functional depth measure for model selection. The methodology's validity is further reinforced by its application to real‐world data, underscoring its effectiveness.
Arefe Asadi, Mitra Fouladirad, Diego Tomassi. An initial investigation for employing ACH depth function in degradation model selection: A case study with real data. Applied Stochastic Models in Business and Industry, 2024, 40 (3), pp.598-619. ⟨10.1002/asmb.2844⟩. ⟨hal-05023362⟩
Journal: Applied Stochastic Models in Business and Industry
Hassan Hachem, Hai Canh Vu, Mitra Fouladirad. Different methods for RUL prediction considering sensor degradation. Reliability Engineering and System Safety, 2023, 243, pp.109897. ⟨10.1016/j.ress.2023.109897⟩. ⟨hal-04543787⟩ Plus de détails...
Predicting the Remaining Useful Lifetime (RUL) of a system has become one of the primary goals of engineering and reliability researchers. RUL prediction is based on the measurement data collected from sensors (e.g. vibration data, temperature data). The collected data is may be inaccurate owing to sensor problems. These problems are often ignored or modeled by a Gaussian noise in most previous work. However, due to various operation circumstances and the aging impact, the sensor itself will ultimately deteriorate and its performance will deteriorate. The Gaussian noise with a constant mean is then not appropriate to fully capture the sensor degradation. In this context, this study focuses on predicting the RUL considering the sensor degradation. For this purpose, a joint model of sensor degradation and system degradation is firstly developed. In this model, the sensor degradation is modeled by Wiener and Gamma processes instead of Gaussian noise. Then, different estimation methods based on the particle filter, a popular model-based technique, were proposed to predict the RUL based on the joint degradation model. To study the performances of our methods, numerical analyzes were carried out. The obtained results confirm the performance and advantages of the proposed methods.
Hassan Hachem, Hai Canh Vu, Mitra Fouladirad. Different methods for RUL prediction considering sensor degradation. Reliability Engineering and System Safety, 2023, 243, pp.109897. ⟨10.1016/j.ress.2023.109897⟩. ⟨hal-04543787⟩
Journal: Reliability Engineering and System Safety
Jingqi Zhang, Mitra Fouladirad, Nikolaos Limnios. A Semi-Markov Model with Geometric Renewal Processes. Methodology and Computing in Applied Probability, 2023, 25 (4), pp.85. ⟨10.1007/s11009-023-10060-z⟩. ⟨hal-04543367⟩ Plus de détails...
We consider a repairable system modeled by a semi-Markov process (SMP), where we include a geometric renewal process for system degradation upon repair, and replacement strategies for non-repairable failure or upon N repairs. First Pérez-Ocón and Torres-Castro studied this system (Pérez-Ocón and Torres-Castro in Appl Stoch Model Bus Ind 18(2):157–170, 2002) and proposed availability calculation using the Laplace Transform. In our work, we consider an extended state space for up and down times separately. This allows us to leverage the standard theory for SMP to obtain all reliability related measurements such as reliability, availability (point and steady-state), mean times and rate of occurrence of failures of the system with general initial law. We proceed with a convolution algebra, which allows us to obtain final closed form formulas for the above measurements. Finally, numerical examples are given to illustrate the methodology.
Jingqi Zhang, Mitra Fouladirad, Nikolaos Limnios. A Semi-Markov Model with Geometric Renewal Processes. Methodology and Computing in Applied Probability, 2023, 25 (4), pp.85. ⟨10.1007/s11009-023-10060-z⟩. ⟨hal-04543367⟩
Journal: Methodology and Computing in Applied Probability
Hasan Misaii, Mitra Fouladirad, Firoozeh Haghighi. Optimal task-driven time-dependent covariate-based maintenance policy. Journal of Computational and Applied Mathematics, 2023, pp.115315. ⟨10.1016/j.cam.2023.115315⟩. ⟨hal-04162527⟩ Plus de détails...
Franck Corset, Mitra Fouladirad, Christian Paroissin. Imperfect condition-based maintenance for a gamma degradation process in presence of unknown parameters. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 2023, 237 (3), pp.546-561. ⟨10.1177/1748006X221134132⟩. ⟨hal-03842177⟩ Plus de détails...
A system subject to degradation is considered. The degradation is modelled by a gamma process. A condition-based maintenance policy with perfect corrective and an imperfect preventive actions is proposed. The maintenance cost is derived considering a Markov-renewal process. The statistical inference of the degradation and maintenance parameters by the maximum likelihood method is investigated. A sensibility analysis to different parameters is carried out and the perspectives are detailed.
Franck Corset, Mitra Fouladirad, Christian Paroissin. Imperfect condition-based maintenance for a gamma degradation process in presence of unknown parameters. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 2023, 237 (3), pp.546-561. ⟨10.1177/1748006X221134132⟩. ⟨hal-03842177⟩
Journal: Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability
Hasan Misaii, Firoozeh Haghighi, Mitra Fouladirad. Opportunistic perfect preventive maintenance policy in presence of masked data. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 2022, 236 (6), pp.1024-1036. ⟨10.1177/1748006X211058936⟩. ⟨hal-04064544⟩ Plus de détails...
In this paper, the maintenance optimization problem of multi-component system is considered. It is assumed that the exact cause of system failure might be masked. That is, the exact cause of failure is unknown, and we only know that it belongs to a set called mask set. Both opportunistic perfect preventive maintenance (OPPM) and perfect corrective maintenance are considered. Threshold of OPPM and inter-inspection interval are considered as decision parameters which are optimized using long-run cost rate criteria. The applicability of the proposed maintenance policy is investigated using an illustrative example.
Hasan Misaii, Firoozeh Haghighi, Mitra Fouladirad. Opportunistic perfect preventive maintenance policy in presence of masked data. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 2022, 236 (6), pp.1024-1036. ⟨10.1177/1748006X211058936⟩. ⟨hal-04064544⟩
Journal: Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability
Fatemeh Safaei, Jafar Ahmadi, Mitra Fouladirad. Optimal N-policy for the maintenance of k-out-of-n systems with dynamic minor repairs considering second-hand component income. International Journal of Production Research, 2022, pp.1-18. ⟨10.1080/00207543.2022.2120107⟩. ⟨hal-04064518⟩ Plus de détails...
This paper proposes a maintenance policy for a k-out-of-n: F system operating to fulfil several jobs without interruptions. The system is replaced when the Nth job completes or at the kth failure, whichever occurs first. So, there are some non-failed components when a replacement is done. These components can be sold as secondhand products to continue working in other systems for a while. The price of them is also considered in the proposed maintenance policy. An optimal maintenance policy is studied to minimise long-run average cost under the constraint of relative mean operating time. Comprehensive numerical studies are done to assess the effect of the model parameters on the optimal solutions. Also, to demonstrate the applicability of the proposed plan, a data set related to wind turbine generator failures is considered as a case study.
Fatemeh Safaei, Jafar Ahmadi, Mitra Fouladirad. Optimal N-policy for the maintenance of k-out-of-n systems with dynamic minor repairs considering second-hand component income. International Journal of Production Research, 2022, pp.1-18. ⟨10.1080/00207543.2022.2120107⟩. ⟨hal-04064518⟩
Journal: International Journal of Production Research
Hoda Kamranfar, Kambiz Ahmadi, Mitra Fouladirad. On inference in a class of exponential distribution under imperfect maintenance. Communications in Statistics - Simulation and Computation, 2022, 53 (7), pp.3368-3394. ⟨10.1080/03610918.2022.2103567⟩. ⟨hal-05023359⟩ Plus de détails...
Hoda Kamranfar, Kambiz Ahmadi, Mitra Fouladirad. On inference in a class of exponential distribution under imperfect maintenance. Communications in Statistics - Simulation and Computation, 2022, 53 (7), pp.3368-3394. ⟨10.1080/03610918.2022.2103567⟩. ⟨hal-05023359⟩
Journal: Communications in Statistics - Simulation and Computation
Mitra Fouladirad, Massimiliano Giorgio, Gianpaolo Pulcini. A transformed gamma process for bounded degradation phenomena. Quality and Reliability Engineering International, 2022, 39 (2), pp.546 - 564. ⟨10.1002/qre.3167⟩. ⟨hal-04063942⟩ Plus de détails...
Most of the stochastic models adopted to describe the evolution over time of degradation phenomena of technological units assume that their degradation level can increase indeterminately. However, these degradation phenomena are typically subjected to obvious bounds, if only because technological units have finite size. In fact, very often, this inconsistency does not significantly affect the effectiveness of unbounded degradation models, since degrading units are usually assumed to fail when their degradation level exceeds a failure threshold that is much smaller than the obvious bounds. Nevertheless, in some cases, due to the very nature of the underlying degradation mechanism, less obvious bounds could exist, which are not necessarily far from the failure thresholds. The question that arises is whether the use of a bounded degradation model, in this latter type of experimental situations, could be beneficial. For this purpose, since a bounded degradation process should necessarily have dependent increments, in this paper we investigate the potential of a new bounded transformed gamma (TG) process to adequately describe bounded degradation phenomena and predict their future evolution. Differently from other existing gamma process based bounded degradation models, here the upper bound is treated as an unknown parameter that has to be estimated from the available degradation data. A numerical example is presented where the parameters of the proposed model are estimated from simulated data. Then the model is applied to a set of wear measures of cylinder liners that equip a diesel engine for marine propulsion, which have also stimulated this study. Model parameters are estimated by using the maximum likelihood (ML) method. The fitting ability of the proposed new bounded process is compared to that of an unbounded gamma process, which was previously adopted to analyze the same liner wear data. Obtained results are critically discussed in the paper.
Mitra Fouladirad, Massimiliano Giorgio, Gianpaolo Pulcini. A transformed gamma process for bounded degradation phenomena. Quality and Reliability Engineering International, 2022, 39 (2), pp.546 - 564. ⟨10.1002/qre.3167⟩. ⟨hal-04063942⟩
Journal: Quality and Reliability Engineering International
J. Etminan, H. Kamranfar, M. Chahkandi, Mitra Fouladirad. Analysis of time-to-failure data for a repairable system subject to degradation. Journal of Computational and Applied Mathematics, 2022, 408, pp.114098. ⟨10.1016/j.cam.2022.114098⟩. ⟨hal-04063947⟩ Plus de détails...
In this paper, a gradually deteriorating system with imperfect repair is considered. The deterioration is modeled by a stationary stochastic process. The system fails once the deterioration level exceeds a given threshold L. At failure, an imperfect repair is performed and the deterioration level is reduced to a fixed value r, say. The system can be repaired n − 1 times and will be replaced after the nth failure. The article aims to estimate the parameters of the proposed deterioration process based on the observed failures. To this end we consider the Wiener and Gamma processes which are the most common used stochastic process models. In Wiener process, an explicit expression for the estimators is obtained. Birnbaum-Saunders approximation is extended to estimate the parameters in Gamma process. An optimal replacement policy is also discussed. Finally, a Monte-Carlo simulation is conducted to investigate the performance of estimators.
J. Etminan, H. Kamranfar, M. Chahkandi, Mitra Fouladirad. Analysis of time-to-failure data for a repairable system subject to degradation. Journal of Computational and Applied Mathematics, 2022, 408, pp.114098. ⟨10.1016/j.cam.2022.114098⟩. ⟨hal-04063947⟩
Journal: Journal of Computational and Applied Mathematics
Hoda Kamranfar, Kambiz Ahmadi, Mitra Fouladirad. On inference in a class of exponential distribution under imperfect maintenance. Communications in Statistics - Simulation and Computation, 2022, pp.1-27. ⟨10.1080/03610918.2022.2103567⟩. ⟨hal-04064552⟩ Plus de détails...
This paper deals with statistical inference for lifetime data in presence of imperfect maintenance. For the maintenance model, the Sheu and Griffith model is considered. The lifetime distribution belongs to exponential distribution class. The maximum likelihood estimation procedure of the model parameters is discussed, and confidence intervals are provided using the asymptotic likelihood theory and bootstrap approach. Based on conjugate and discrete priors, Bayesian estimators of the model parameters are developed under symmetric and asymmetric loss functions. The proposed methodologies are applied to simulated data and sensitivity analysis to different parameters and data characteristics is carried out. The effect of model misspecification is also assessed within this class of distributions through a Monte Carlo simulation study. Finally, two datasets are analyzed for demonstrative aims.
Hoda Kamranfar, Kambiz Ahmadi, Mitra Fouladirad. On inference in a class of exponential distribution under imperfect maintenance. Communications in Statistics - Simulation and Computation, 2022, pp.1-27. ⟨10.1080/03610918.2022.2103567⟩. ⟨hal-04064552⟩
Journal: Communications in Statistics - Simulation and Computation
Marwa Belhaj Salem, Mitra Fouladirad, Estelle Deloux. Variance Gamma process as degradation model for prognosis and imperfect maintenance of centrifugal pumps. Reliability Engineering and System Safety, 2022, 223, pp.108417. ⟨10.1016/j.ress.2022.108417⟩. ⟨hal-04063946⟩ Plus de détails...
This paper considers the degradation modelling of a non-monotonous health indicator. A Variance Gamma process is proposed for the degradation modelling and its calibration in presence of data is discussed. The remaining useful lifetime estimation based on this model is considered and its sensitivity to parameters estimates is analysed. The model is applied to real data of leakage rate of centrifugal pump. Eventually, an imperfect maintenance policy is proposed and optimized.
Marwa Belhaj Salem, Mitra Fouladirad, Estelle Deloux. Variance Gamma process as degradation model for prognosis and imperfect maintenance of centrifugal pumps. Reliability Engineering and System Safety, 2022, 223, pp.108417. ⟨10.1016/j.ress.2022.108417⟩. ⟨hal-04063946⟩
Journal: Reliability Engineering and System Safety
Hasan Misaii, Firoozeh Haghighi, Mitra Fouladirad. Optimal shock‐based maintenance policy for a system in a dynamic environment. Applied Stochastic Models in Business and Industry, 2022, 38 (6), pp.918 - 934. ⟨10.1002/asmb.2686⟩. ⟨hal-04063939⟩ Plus de détails...
In this article, we consider a single-unit system that operates in a dynamic environment and is subject to shocks. Shocks only affect the system (nonlethal shock) and do not cause sudden failure, and arrive according to a counting process. Both homogeneous and nonhomogeneous Poisson processes are considered for shocks arrival modeling. In order to model the dynamic environment and consider shock effects, a multiplicative failure rate model is proposed. Both corrective maintenance and shock-based preventive maintenance are considered, and two policies are proposed. In the first proposed policy, the system is replaced by a new one upon a failure or based on the predetermined number of shocks, whichever comes first, while the second proposed policy extends the first one by considering an imperfect preventive repair at each inspection time. The inspection times are periodic and the interinspection interval is considered as a decision variable. The proposed policies are optimized according to long-run cost rate criteria. Numerical examples illustrate the applicability and efficiency of the proposed policies.
Hasan Misaii, Firoozeh Haghighi, Mitra Fouladirad. Optimal shock‐based maintenance policy for a system in a dynamic environment. Applied Stochastic Models in Business and Industry, 2022, 38 (6), pp.918 - 934. ⟨10.1002/asmb.2686⟩. ⟨hal-04063939⟩
Journal: Applied Stochastic Models in Business and Industry
