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Viliam Makis - One of the best experts on this subject based on the ideXlab platform.
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optimal condition based and age based opportunistic Maintenance Policy for a two unit series system
Computers & Industrial Engineering, 2019Co-Authors: Viliam Makis, Jingjing Wang, Xian ZhaoAbstract:Abstract A new optimal Maintenance Policy considering the condition monitoring and age information is considered for a two-unit repairable system. Unit 1 is the core component of the system, which is subject to soft failure observed only through inspections. Unit 2 is subject to hard failure and the age information representing usage of unit 2 is available. Unlike the previous Maintenance models where Maintenance actions can be initiated only at the inspection epochs, we assume that corrective Maintenance action would be carried out immediately when unit 2 fails. Furthermore, a preventive Maintenance is performed on the units if the deterioration level of unit 1 or the usage of unit 2 exceeds certain Maintenance threshold for that unit. Under this Maintenance strategy, when one of the two units is correctively or preventively maintained, there is an opportunity to maintain the other unit. The Maintenance problem is formulated and solved in the semi-Markov decision process framework. A formula for the average Maintenance cost is derived and the optimal thresholds for preventive and opportunistic Maintenance of the two units minimizing the long run expected average cost are determined. A practical example of a two-unit wind turbine system is provided, and a comparison analysis with other Maintenance policies shows an outstanding performance of the proposed Policy.
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an integrated framework for health measures prediction and optimal Maintenance Policy for mechanical systems using a proportional hazards model
Mechanical Systems and Signal Processing, 2018Co-Authors: Viliam Makis, Chaoqun Duan, Chao DengAbstract:Abstract This paper considers an integrated framework for health measures prediction and optimal Maintenance Policy for mechanical systems subject to condition monitoring (CM) and random failure. We propose the proportional hazards model (PHM) to consider CM information as well as the age of the mechanical systems. Although the form of health prediction for the mechanical systems under periodic monitoring in the PHM with Markov chain was developed previously, the case of the continuous-state degradation process allowing possible degradation between the inspections still has not appeared. To this aim, the paper allows the use of Gamma process with non-constant degradation, which broadens the application area of PHM. A matrix-based approximation method is employed to compute health measures of the machine, such as condition reliability, mean residual life, residual life distribution. Based on the health measures, the optimal Maintenance Policy, which considers both hazard rate control limit and age control limit, is proposed and the optimization problem is formulated and solved in a semi-Markov decision process (SMDP) framework. The objective is to minimize the long-run expected average cost. The method is illustrated using two real data sets obtained from feed subsystem of a boring machine and GaAs lasers collected at regular time epochs, respectively. A comparison with other methods is given, which illustrates the effectiveness of our approach.
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joint optimization of Maintenance Policy and inspection interval for a multi unit series system using proportional hazards model
Journal of the Operational Research Society, 2018Co-Authors: Leila Jafari, Farnoosh Naderkhani, Viliam MakisAbstract:Unlike the previous Maintenance models of multi-unit systems which considered condition-based Maintenance (CBM) or age information separately, we propose a novel optimization model which is characterized by a combination of CBM and age information using proportional hazards model. The preventive Maintenance is applied for the main two units, where one unit is the core part of the system and subject to CM, and only the age information for the second main unit is available. Also, the other units are adjusted or replaced each time when the system is maintained. The objective is to find an optimal opportunistic Maintenance Policy minimizing the long-run expected average cost per unit time. The problem is formulated and solved in the semi-Markov decision process framework. The formula for the mean residual life of the system is derived, which is an important statistic in practical applications. A practical example of a multi-unit system from a mining company is provided, and a comparison with other policies shows an outstanding performance of the new model and the control Policy proposed in this paper.
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optimal preventive and opportunistic Maintenance Policy for a two unit system
The International Journal of Advanced Manufacturing Technology, 2017Co-Authors: Nooshin Salari, Viliam MakisAbstract:This paper presents a new optimal opportunistic and preventive Maintenance Policy for a two-unit model with economic dependency applicable to the electric power distribution systems. Unlike the previous optimal Maintenance policies which considered mainly single unit systems or no opportunistic Maintenance for two-unit systems, we consider a two-unit system with economic dependency, where unit 1 is subject to condition monitoring and soft failure and unit 2 is subject to hard failure. Unit 1 is gradually deteriorating and unit 2 has a general life time distribution. Condition of unit 1 is monitored periodically and it is considered as failed when its deterioration level reaches a critical level N. At the failure time of unit 2 system is considered as failed, although unit 1 is working, and unit 2 will be correctively replaced by the next inspection epoch. Units 1 or 2 are preventively replaced when deterioration level of unit 1 or age of unit 2 reaches or exceeds the related PM levels. At the time of corrective or preventive replacement of a unit, there is an opportunity to replace also the other unit. A mathematical model is derived to find the preventive and opportunistic replacement levels for units 1 and 2 that minimize the long run expected average cost per unit time. The problem is formulated and solved in the semi-Markov decision process (SMDP) framework. Numerical example is provided to illustrate the performance of the proposed model and a comparison of the proposed model with other policies is carried out.
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optimal bayesian Maintenance Policy and early fault detection for a gearbox operating under varying load
Journal of Vibration and Control, 2016Co-Authors: Chen Lin, Viliam MakisAbstract:Due to the advancements in data measurement and computer technology, automated data collection from multiple sensors has become common in recent years. However, very few papers have dealt with the cost-optimal early fault detection of gearboxes, condition based Maintenance Policy, and remaining useful life prediction when multiple sensors are used for data collection under varying load. The novel approach presented here is based on vector autoregressive vibration signal modeling and continuous time hidden Markov modeling using the optimal Bayesian control technique. System condition is modeled using a continuous time Markov chain with three states, namely, unobservable healthy state 0, unobservable warning state 1 and observable failure state 2. Model parameters are calculated using the expectation-maximization algorithm. The optimal control Policy for the three-state model is represented by a Bayesian control chart for a multivariate observation process. The chart monitors the posterior probability that ...
Christophe Berenguer - One of the best experts on this subject based on the ideXlab platform.
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predictive Maintenance Policy for a gradually deteriorating system subject to stress
Reliability Engineering & System Safety, 2009Co-Authors: Estelle Deloux, Bruno Castanier, Christophe BerenguerAbstract:This paper deals with a predictive Maintenance Policy for a continuously deteriorating system subject to stress. We consider a system with two failure mechanisms which are, respectively, due to an excessive deterioration level and a shock. To optimize the Maintenance Policy of the system, an approach combining statistical process control (SPC) and condition-based Maintenance (CBM) is proposed. CBM Policy is used to inspect and replace the system according to the observed deterioration level. SPC is used to monitor the stress covariate. In order to assess the performance of the proposed Maintenance Policy and to minimize the long-run expected Maintenance cost per unit of time, a mathematical model for the maintained system cost is derived. Analysis based on numerical results are conducted to highlight the properties of the proposed Maintenance Policy in respect to the different Maintenance parameters.
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A condition-based Maintenance Policy with non-periodic inspections for a two-unit series system
Reliability Engineering and System Safety, 2005Co-Authors: Bruno Castanier, Antoine Grall, Christophe BerenguerAbstract:This paper considers a condition-based Maintenance Policy for a two-unit deteriorating system. Each unit is subject to gradual deterioration and is monitored by sequential non-periodic inspections. It can be maintained by good as new preventive or corrective replacements. Every inspection or replacement entails a set-up cost and a component-specific unit cost but if actions on the two components are combined, the set-up cost is charged only once. A parametric Maintenance decision framework is proposed to coordinate inspection/replacement of the two components and minimize the long-run Maintenance cost of the system. A stochastic model is developed on the basis of the semi-regenerative properties of the maintained system state and the associated cost model is used to assess and optimize the performance of the Maintenance model. Numerical experiments emphasize the interest of a control of the operation groupings.
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a sequential condition based repair replacement Policy with non periodic inspections for a system subject to continuous wear
Applied Stochastic Models in Business and Industry, 2003Co-Authors: Bruno Castanier, Christophe Berenguer, Antoine GrallAbstract:This paper studies a condition-based Maintenance Policy for a repairable system subject to a continuous-state gradual deterioration monitored by sequential non-periodic inspections. The system can be maintained using different Maintenance operations (partial repair, as good as new replacement) with different effects (on the system state), costs and durations. A parametric decision framework (multi-threshold Policy) is proposed to choose sequentially the best Maintenance actions and to schedule the future inspections, using the on-line monitoring information on the system deterioration level gained from the current inspection. Taking advantage of the semi-regenerative (or Markov renewal) properties of the maintained system state, we construct a stochastic model of the time behaviour of the maintained system at steady state. This stochastic model allows to evaluate several performance criteria for the Maintenance Policy such as the long-run system availability and the long-run expected Maintenance cost. Numerical experiments illustrate the behaviour of the proposed condition-based Maintenance Policy. Copyright © 2003 John Wiley & Sons, Ltd.
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Maintenance Policy for a continuously monitored deteriorating system
Probability in the Engineering and Informational Sciences, 2003Co-Authors: Christophe Berenguer, Antoine Grall, Laurence Dieulle, Michel RoussignolAbstract:We consider a continuously monitored system that gradually and stochastically deteriorates. An alarm threshold is set on the system deterioration level for triggering a delayed preventive Maintenance operation. A mathematical model is developed to find the value of the alarm threshold that minimizes the asymptotic unavailability. Approximations are derived to improve the numerical optimization.
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A condition-based Maintenance Policy for stochastically deteriorating systems
Reliability Engineering and System Safety, 2002Co-Authors: Antoine Grall, Christophe Berenguer, Laurence DieulleAbstract:We focus on the analytical modeling of a condition-based inspection/replacement Policy for a stochastically and continuously deteriorating single-unit system. We consider both the replacement threshold and the inspection schedule as decision variables for this Maintenance problem and we propose to implement the Maintenance Policy using a multi-level control-limit rule. In order to assess the performance of the proposed Maintenance Policy and to minimize the long run expected Maintenance cost per unit time, a mathematical model for the maintained system cost is derived, supported by the existence of a stationary law for the maintained system state. Numerical experiments illustrate the performance of the proposed Policy and confirm that the Maintenance cost rate on an infinite horizon can be minimized by a joint optimization of the Maintenance structure thresholds, or equivalently by a joint optimization of a system replacement threshold and the aperiodic inspection schedule.
Rui Peng - One of the best experts on this subject based on the ideXlab platform.
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jointly optimizing lot sizing and Maintenance Policy for a production system with two failure modes
Reliability Engineering & System Safety, 2020Co-Authors: Kaiye Gao, Rui PengAbstract:Abstract In the reliability literature, studies that jointly investigate Maintenance and production are typically restricted to one failure mode and fail to address the case where multiple failure modes may exist. This study investigates the problem of joint optimization of lot sizing and Maintenance Policy for a multi-product production system subject to two failure modes. The failure of the first mode is a soft failure that occurs after defects arrive. The failure of the second mode is a hard failure that occurs without any early warning signals. Products are sequentially produced by the system and a complete run of all products forms a production cycle. The system needs to be re-set up before producing a different product. Both the production cycle and the time of set-up depend on the lot sizes of products. Models are proposed for two Maintenance policies: 1) arranging the Maintenance during the set-up at the end of each production cycle; 2) arranging the Maintenance during each of set-ups. The expected profit per unit time is formulated to obtain the optimal lot sizing and Maintenance Policy. Some properties of the proposed models are provided and they show that the optimal lot sizing and Maintenance Policy can be obtained under certain conditions. Case studies and sensitivity analyses are presented to illustrate the proposed models of two Maintenance policies. The results show that the manufacturer will gain the most profit if the optimal lot sizing and Maintenance Policy are adopted. The results of comparing both Maintenance policies reveal that the excessive Maintenance is not cost-effective. The sensitivity analyses illustrate that reducing the cost due to failures and improving system reliability are effective ways to increase the expected profit per time unit.
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a two phase preventive Maintenance Policy considering imperfect repair and postponed replacement
European Journal of Operational Research, 2019Co-Authors: Li Yang, Zhisheng Ye, Sufen Yang, Rui PengAbstract:Abstract This paper investigates a novel two-phase preventive Maintenance Policy for a single-component system with an objective of maximizing the revenue generated by the performance-based contracting (PBC). The system undergoes a defective state before failure, and produces signal hinting the condition. The Maintenance Policy consists of two phases: imperfect Maintenance phase followed by postponed replacement phase. In the imperfect Maintenance phase, inspection is performed to reveal the defective state, leading to a possible repair. Both the inspection and the repair are imperfect. In the postponed replacement phase, preventive replacement is performed during the upcoming scheduled Maintenance window, before which no inspection or repair is executed. The expected net revenue under PBC is maximized via the joint optimization of the inspection interval, number of inspection and preventive replacement interval. We apply the model to a case from a steel converter plant, and the results show that our proposed Maintenance Policy outperforms some existing Maintenance policies in terms of the net revenue.
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a preventive Maintenance Policy based on dependent two stage deterioration and external shocks
Reliability Engineering & System Safety, 2017Co-Authors: Li Yang, Rui Peng, Qingqing Zhai, Yu ZhaoAbstract:Abstract This paper proposes a preventive Maintenance Policy for a single-unit system whose failure has two competing and dependent causes, i.e., internal deterioration and sudden shocks. The internal failure process is divided into two stages, i.e. normal and defective. Shocks arrive according to a non-homogeneous Poisson process (NHPP), leading to the failure of the system immediately. The occurrence rate of a shock is affected by the state of the system. Both an age-based replacement and finite number of periodic inspections are schemed simultaneously to deal with the competing failures. The objective of this study is to determine the optimal preventive replacement interval, inspection interval and number of inspections such that the expected cost per unit time is minimized. A case study on oil pipeline Maintenance is presented to illustrate the Maintenance Policy.
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optimal preventive Maintenance Policy with consideration of production wait
Journal of Shanghai Jiaotong University (science), 2015Co-Authors: Wenbin Wang, Rui PengAbstract:In this paper, we consider the replacement of a single unit with catastrophic failure mode. Besides replaced at a preset time, the unit is also replaced at failure time or if it encounters a production wait and its age has reached a threshold. The joint preventive Maintenance interval and threshold optimization problem are formulated with the objective of minimizing the expected cost per unit time in long run. A numerical example is presented to illustrate the applicability of the model.
Laurence Dieulle - One of the best experts on this subject based on the ideXlab platform.
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a condition based Maintenance Policy for multi component systems with levy copulas dependence
Reliability Engineering & System Safety, 2016Co-Authors: Estelle Deloux, Laurence DieulleAbstract:Abstract In this paper, we propose a new condition-based Maintenance Policy for multi-component systems taking into account stochastic and economic dependences. The stochastic dependence between components due to common environment is modelled by Levy copulas. Its influence on the Maintenance optimization is investigated with different dependence degrees. On the issue of economic dependence providing opportunities to group Maintenance activities, a new Maintenance decision rule is proposed which permits Maintenance grouping. In order to evaluate the performance of the proposed Maintenance Policy, we compare it to the classical Maintenance policies.
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Maintenance Policy for a continuously monitored deteriorating system
Probability in the Engineering and Informational Sciences, 2003Co-Authors: Christophe Berenguer, Antoine Grall, Laurence Dieulle, Michel RoussignolAbstract:We consider a continuously monitored system that gradually and stochastically deteriorates. An alarm threshold is set on the system deterioration level for triggering a delayed preventive Maintenance operation. A mathematical model is developed to find the value of the alarm threshold that minimizes the asymptotic unavailability. Approximations are derived to improve the numerical optimization.
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A condition-based Maintenance Policy for stochastically deteriorating systems
Reliability Engineering and System Safety, 2002Co-Authors: Antoine Grall, Christophe Berenguer, Laurence DieulleAbstract:We focus on the analytical modeling of a condition-based inspection/replacement Policy for a stochastically and continuously deteriorating single-unit system. We consider both the replacement threshold and the inspection schedule as decision variables for this Maintenance problem and we propose to implement the Maintenance Policy using a multi-level control-limit rule. In order to assess the performance of the proposed Maintenance Policy and to minimize the long run expected Maintenance cost per unit time, a mathematical model for the maintained system cost is derived, supported by the existence of a stationary law for the maintained system state. Numerical experiments illustrate the performance of the proposed Policy and confirm that the Maintenance cost rate on an infinite horizon can be minimized by a joint optimization of the Maintenance structure thresholds, or equivalently by a joint optimization of a system replacement threshold and the aperiodic inspection schedule.
Leila Jafari - One of the best experts on this subject based on the ideXlab platform.
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joint optimization of Maintenance Policy and inspection interval for a multi unit series system using proportional hazards model
Journal of the Operational Research Society, 2018Co-Authors: Leila Jafari, Farnoosh Naderkhani, Viliam MakisAbstract:Unlike the previous Maintenance models of multi-unit systems which considered condition-based Maintenance (CBM) or age information separately, we propose a novel optimization model which is characterized by a combination of CBM and age information using proportional hazards model. The preventive Maintenance is applied for the main two units, where one unit is the core part of the system and subject to CM, and only the age information for the second main unit is available. Also, the other units are adjusted or replaced each time when the system is maintained. The objective is to find an optimal opportunistic Maintenance Policy minimizing the long-run expected average cost per unit time. The problem is formulated and solved in the semi-Markov decision process framework. The formula for the mean residual life of the system is derived, which is an important statistic in practical applications. A practical example of a multi-unit system from a mining company is provided, and a comparison with other policies shows an outstanding performance of the new model and the control Policy proposed in this paper.
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joint optimization of lot sizing and Maintenance Policy for a partially observable two unit system
The International Journal of Advanced Manufacturing Technology, 2016Co-Authors: Leila Jafari, Viliam MakisAbstract:In this paper, we present a new model to find the jointly optimal economic manufacturing quantity (EMQ) and preventive Maintenance (PM) Policy for a complex production facility. Unlike the previous joint models which dealt with EMQ and Maintenance Policy considering a single unit production facility and traditional Maintenance approaches, we consider a production facility which consists of two modules with economic dependence. The more expensive module (unit 1) is subject to condition monitoring (CM), and only the age information of the second module (unit 2) is available, which follows a general distribution. The deterioration process of unit 1 is modeled as a continuous time hidden-Markov process. CM data is available at the end of each production run, and it provides only partial information about the hidden state of unit 1. The failure state of unit 1 is observable at any time. The objective is to develop a jointly optimal lot sizing and Maintenance Policy for a two-unit production facility using multivariate Bayesian control approach by minimizing the long-run expected average cost per unit time. The problem is formulated and solved in the semi-Markov decision process (SMDP) framework. Also, a formula for the mean residual life (MRL) of the production facility is derived, which is an important statistic for practical applications. A practical example of the wind turbine CM and Maintenance is provided and a comparison with other policies shows an outstanding performance of the new model and the control Policy proposed in this paper.
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optimal lot sizing and Maintenance Policy for a partially observable production system
Computers & Industrial Engineering, 2016Co-Authors: Leila Jafari, Viliam MakisAbstract:Joint development of the EMQ model of a deteriorating system and CBM.Consideration of both Maintenance and production-related costs.Hidden Markov modeling of the partially observable production system.Development of the semi-Markov decision process and the optimization algorithm.Numerical studies and comparisons show an excellent performance. In this paper, we present a joint optimization of economic manufacturing quantity (EMQ) and Maintenance Policy for a production facility subject to deterioration and condition monitoring (CM) at the times the production runs are completed. The production facility deterioration is described by a hidden continuous-time Markov process. CM provides partial information about the hidden state of the production facility. The objective is to develop a jointly optimal lot sizing and Maintenance Policy using multivariate Bayesian control approach. The posterior probability statistic is updated at each sampling epoch using Bayes' rule. When the posterior probability crosses a control limit, the production system is stopped and full inspection is initiated, followed possibly by preventive Maintenance (PM). Production will resume when all available inventory is depleted or when PM action is completed, whichever occurs later. We also assume that the production and demand rates are constant over time. The problem is formulated and solved in the semi-Markov decision process (SMDP) framework. The objective is to minimize the long-run expected average cost per unit time. The shortage and set-up costs are considered in the model along with the Maintenance, inventory holding, and lost production costs. A numerical example is provided and a sensitivity analysis is performed. A comparison with the age-based Maintenance Policy shows an outstanding performance of the new model and the control Policy proposed in this paper.
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joint optimal lot sizing and preventive Maintenance Policy for a production facility subject to condition monitoring
International Journal of Production Economics, 2015Co-Authors: Leila Jafari, Viliam MakisAbstract:Abstract In this paper, we consider the joint optimization of economic manufacturing quantity (EMQ) and preventive Maintenance (PM) Policy for a production facility subject to deterioration and condition monitoring (CM). Unlike the previous joint models of EMQ and Maintenance Policy which used traditional Maintenance approaches, we propose the proportional hazards model (PHM) to consider CM information as well as the age of the production facility. The deterioration process is determined by the age and covariate values and the covariate process is modeled as a continuous-time Markov process. The condition information is available at each inspection epoch, which is the end of each production run. The hazard rate is estimated after obtaining the new information through CM. The problem is formulated and solved in the semi-Markov decision process (SMDP) framework. The objective is to minimize the long-run expected average cost per unit time. Also, the mean residual life (MRL) of the production facility is calculated as an important statistic for practical applications. A numerical example is provided and a comparison with the age-based Policy shows an outstanding performance of the new model and the control Policy proposed in this paper.
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Optimal Maintenance Policy and residual life estimation for a slowly degrading system subject to condition monitoring
Reliability Engineering & System Safety, 2015Co-Authors: Diyin Tang, Viliam Makis, Leila JafariAbstract:Abstract In this paper, we present an optimal preventive Maintenance Policy and develop a procedure for residual life estimation for a slowly degrading system subject to soft failure and condition monitoring at equidistant, discrete time epochs. An autoregressive model with time effect is considered to describe the system degradation, which utilizes both the system current age and the previous state observations. The class of control-limit Maintenance policies with two different inspection strategies is considered, and the optimization problem is formulated and solved in a semi-Markov decision process framework. The objective is to minimize the long-run expected average cost. A formula for the mean residual life is derived for the proposed degradation model and a control limit Policy, which enables the estimation of the remaining useful life and early Maintenance planning based on the observed degradation process. An example is presented to demonstrate the effectiveness of the proposed method.
