11 research outputs found
Π€ΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ ΡΠ΅Π½Π½ΠΎΡΡΠΈ Π² ΡΠΈΡΡΠ΅ΠΌΠ΅ ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΡΡΠ²Π΅Π½Π½ΡΠΌΠΈ Π°ΠΊΡΠΈΠ²Π°ΠΌΠΈ ΡΠ»Π΅ΠΊΡΡΠΎΡΠ½Π΅ΡΠ³Π΅ΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΊΠΎΠΌΠΏΠ°Π½ΠΈΠΈ
Π¦Π΅Π»ΡΡ ΡΡΠ°ΡΡΠΈ ΡΠ²Π»ΡΠ΅ΡΡΡ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠ° ΠΌΠΎΠ΄Π΅Π»ΠΈ, ΠΎΠΏΠΈΡΡΠ²Π°ΡΡΠ΅ΠΉ ΠΏΡΠΎΡΠ΅ΡΡ ΡΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΡΠ΅Π½Π½ΠΎΡΡΠΈ Π² ΡΠΈΡΡΠ΅ΠΌΠ΅ ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΡΡΠ²Π΅Π½Π½ΡΠΌΠΈ Π°ΠΊΡΠΈΠ²Π°ΠΌΠΈ ΡΠ»Π΅ΠΊΡΡΠΎΡΠ½Π΅ΡΠ³Π΅ΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΊΠΎΠΌΠΏΠ°Π½ΠΈΠΈ. ΠΠΏΡΠ΅Π΄Π΅Π»ΡΡΡΡΡ ΠΊΠ»ΡΡΠ΅Π²ΡΠ΅ ΠΏΡΠΎΠ±Π»Π΅ΠΌΡ, Ρ ΠΊΠΎΡΠΎΡΡΠΌΠΈ ΡΡΠ°Π»ΠΊΠΈΠ²Π°ΡΡΡΡ ΠΊΠΎΠΌΠΏΠ°Π½ΠΈΠΈ ΡΠ»Π΅ΠΊΡΡΠΎΡΠ½Π΅ΡΠ³Π΅ΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΎΡΡΠ°ΡΠ»ΠΈ Π² ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΠΈ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΡΡΠ²Π΅Π½Π½ΡΠΌΠΈ Π°ΠΊΡΠΈΠ²Π°ΠΌΠΈ Ρ ΡΡΠ΅ΡΠΎΠΌ ΠΈΠ·ΠΌΠ΅Π½ΡΡΡΠΈΡ
ΡΡ ΡΡΠ»ΠΎΠ²ΠΈΠΉ Π²Π½Π΅ΡΠ½Π΅ΠΉ ΡΡΠ΅Π΄Ρ. ΠΡΠ΄Π΅Π»ΡΠ΅ΡΡΡ Π·Π½Π°ΡΠΈΠΌΠΎΡΡΡ ΡΠ°Π·Π²ΠΈΡΠΈΡ ΡΠ΅Π½Π½ΠΎΡΡΠ½ΠΎΠ³ΠΎ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄Π° ΠΏΡΠΈΠΌΠ΅Π½ΠΈΡΠ΅Π»ΡΠ½ΠΎ ΠΊ ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΡΡΠ²Π΅Π½Π½ΡΠΌΠΈ Π°ΠΊΡΠΈΠ²Π°ΠΌΠΈ. ΠΠ½Π°Π»ΠΈΠ·ΠΈΡΡΠ΅ΡΡΡ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΡ ΠΏΡΠΈΠ»ΠΎΠΆΠ΅Π½ΠΈΡ ΠΏΠΎΠ»ΠΎΠΆΠ΅Π½ΠΈΠΉ ΡΠ΅ΠΎΡΠΈΠΈ ΡΠΈΡΡΠ΅ΠΌ ΠΊ ΠΏΡΠΎΡΠ΅ΡΡΡ ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΡΡΠ²Π΅Π½Π½ΡΠΌΠΈ Π°ΠΊΡΠΈΠ²Π°ΠΌΠΈ. ΠΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½Π° Π°Π²ΡΠΎΡΡΠΊΠ°Ρ ΠΌΠΎΠ΄Π΅Π»Ρ ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΡΡΠ²Π΅Π½Π½ΡΠΌΠΈ Π°ΠΊΡΠΈΠ²Π°ΠΌΠΈ ΡΠ»Π΅ΠΊΡΡΠΎΡΠ½Π΅ΡΠ³Π΅ΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΊΠΎΠΌΠΏΠ°Π½ΠΈΠΈ. ΠΠ»Π΅ΠΌΠ΅Π½ΡΡ Π½ΠΎΠ²ΠΈΠ·Π½Ρ Π·Π°ΠΊΠ»ΡΡΠ°ΡΡΡΡ Π² Π²ΡΠ΄Π΅Π»Π΅Π½ΠΈΠΈ Π΄ΡΠ°ΠΉΠ²Π΅ΡΠΎΠ² ΡΠΎΠ·Π΄Π°Π½ΠΈΡ ΡΠ΅Π½Π½ΠΎΡΡΠΈ Π½Π° Π²ΡΠ΅Ρ
ΡΡΠΎΠ²Π½ΡΡ
ΠΊΠΎΡΠΏΠΎΡΠ°ΡΠΈΠ²Π½ΠΎΠ³ΠΎ ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ, Π° ΡΠ°ΠΊΠΆΠ΅ Π² ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠΈ ΠΏΠΎΠ»ΠΎΠΆΠ΅Π½ΠΈΠΉ ΡΠΈΡΡΠ΅ΠΌΠ½ΠΎΠ³ΠΎ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄Π° Π΄Π»Ρ ΠΎΠΏΠΈΡΠ°Π½ΠΈΡ ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΡΡΠ²Π΅Π½Π½ΡΠΌΠΈ Π°ΠΊΡΠΈΠ²Π°ΠΌΠΈ Ρ ΡΠΎΡΠΊΠΈ Π·ΡΠ΅Π½ΠΈΡ ΠΎΡΠΊΡΡΡΠΎΠΉ ΡΠΈΡΡΠ΅ΠΌ
Condition-based maintenance for systems with aging and cumulative damage based on proportional hazards model
This paper develops a condition-based maintenance (CBM) policy for systems subject to aging and cumulative damage. The cumulative damage is modeled by a continuous degradation process. Different from previous studies which assume that the system fails when the degradation level exceeds a specific threshold, this paper argues that the degradation itself does not directly lead to system failure, but increases the failure risk of the system. Proportional hazards model (PHM) is employed to characterize the joint effect of aging and cumulative damage. CBM models are developed for two cases: one assumes that the distribution parameters of the degradation process are known in advance, while the other assumes that the parameters are unknown and need to be estimated during system operation. In the first case, an optimal maintenance policy is obtained by minimizing the long-run cost rate. For the case with unknown parameters, periodic inspection is adopted to monitor the degradation level of the system and update the distribution parameters. A case study of Asphalt Plug Joint in UK bridge system is employed to illustrate the maintenance policy.The work described in this paper was partially supported by a theme-based project grant (T32-101/15-R) of University Grants Council, and a Key Project (71532008) supported by National Natural Science Foundation of China
Reliability modeling and preventive maintenance of load-sharing systems with degrading components
This article presents certain new approaches to the reliability modeling of systems subject to shared loads. It is assumed that components in the system degrade continuously through an additive impact under load. The reliability assessment of such systems is often complicated by the fact that both the arriving load and the failure of components influence the degradation of the surviving components in a complex manner. The proposed approaches seek to ease this problem, by first deriving the time to prior failures and the arrival of random loads and then determining the number of failed components. Two separate models capable of analyzing system reliability as well as arriving at system maintenance and design decisions are proposed. The first considers a constant load and the other a cumulative load. A numerical example is presented to illustrate the effectiveness of the proposed models
An imperfect maintenance policy for mission-oriented systems subject to degradation and external shocks
This paper develops a maintenance model for mission-oriented systems subject to natural degradation and external shocks. For mission-oriented systems which are used to perform safety-critical tasks, maintenance actions need to satisfy a range of constraints such as availability/reliability, maintenance duration and the opportunity of maintenance. Additionally, in developing maintenance policy, one needs to consider the natural degradation due to aging and wearing along with the external shocks due to variations of the operating environment. In this paper, the natural degradation is modeled as a Wiener process and the arrival of random shock as a homogeneous Poisson process. The damage caused by shocks is integrated into the degradation process, according to the cumulative shock model. Improvement factor model is used to characterize the impact of maintenance actions on system restoration. Optimal maintenance policy is obtained by minimizing the long-run cost rate. Finally, an example of subsea blowout preventer system is presented to illustrate the effectiveness of the proposed model
A condition-based maintenance policy for degrading systems with age- and state-dependent operating cost
Most of the maintenance policies in existing publications assume that no cost is incurred as long as the system can undertake missions while little consideration has been devoted to the operating cost during system operation. However, in practice, the operating cost increases while the system ages and degrades even if a system is in a functioning state. This paper proposes a maintenance policy for a degrading system with age- and state-dependent operating cost, which increases with system age and degradation levels. Under such a setting, a replacement model is first developed to investigate the optimal preventive replacement policy. The replacement model is then extended to a repair-replacement model, in which imperfect repair is assumed to restore the system to the operating condition. Particularly, the repair model with controllable and uncontrollable repair levels is considered separately. The paper proves that the optimal maintenance policy is actually a monotone control limit policy, where the optimal control limits decrease monotonically with system age. Finally, a numerical example along with sensitivity analysis is presented to illustrate the optimal maintenance policy. The proposed model implies a more conservative maintenance policy, compared with the traditional model without the age- and state-dependent operating cost
Maintenance scheduling for multicomponent systems with hidden failures
This paper develops a maintenance policy for a multicomponent system subject to hidden failures. Components of the system are assumed to suffer from hidden failures, which can only be detected at inspection. The objective of the maintenance policy is to determine the inspection intervals for each component such that the long-run cost rate is minimized. Due to the dependence among components, an exact optimal solution is difficult to obtain. Concerned with the intractability of the problem, a heuristic method named βbase interval approachβ is adopted to reduce the computational complexity. Performance of the base interval approach is analyzed, and the result shows that the proposed policy can approximate the optimal policy within a small factor. Two numerical examples are presented to illustrate the effectiveness of the policy
A restless bandit approach for capacitated condition based maintenance scheduling
peer reviewedThis paper considers the maintenance scheduling problem of multiple non-identical machines deteriorating over time. The deterioration gradually decreases a machineβs performance, which results in revenue losses due to lower output quality. The maintenance cost is dependent on the degradation state, and the number of maintenance activities that can be carried out simultaneously is restricted by the number of maintenance workers. Our main goal is to propose a heuristic with low complexity that consistently produces solutions close to the optimal strategy for problems of real size. We cast the problem as a restless bandit problem and propose an index based heuristic (Whittleβs index policy) which can be computed efficiently. We also provide a lower bound that can be computed by linear programming. We numerically compare the performance of the index heuristic with alternative policies. In addition to achieving superior performance over failure-based and threshold policies, Whittleβs policy numerically converges to our lower bound when the number of machines is moderately high and/or maintenance workload is high
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A review of asset management literature on multi-asset systems
This article gives an overview of the literature on asset management for multi-unit systems with an emphasis on two multi-asset categories: fleet (a system of homogeneous assets) and portfolio (a system of heterogeneous assets). As asset systems become more complicated, researchers have employed different terms to refer to their specific problems. With an
objective to facilitate readers in searching conducive studies to their interests, this paper establishes a novel classification scheme for multi-unit systems in accordance with essential features such as diversity of assets and intervention options. Moreover, discerning differences in characteristics between cross-component and cross-asset interactions, we select three types of potential multi-component dependencies (performance, stochastic, and resource) and extend their notions to be applicable to multi-asset systems. The investigation into these dependencies enables the identification of problems that could exist in real industrial settings
but are yet to be determined in academia. Ultimately, we delve into modelling approaches adopted by previous researchers. This comprehensive information allows us to offer the insights into the current trends in multi-asset maintenance. We expect that the output of this review paper will not only stress research gaps on multi-asset systems, but more importantly
help systematise future studies on this aspect
Development of an advanced artificial intelligent reliability analysis tool to enhance ship operations and maintenance activities
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Establishment of a novel predictive reliability assessment strategy for ship machinery
There is no doubt that recent years, maritime industry is moving forward to novel and sophisticated inspection and maintenance practices. Nowadays maintenance is encountered as an operational method, which can be employed both as a profit generating process and a cost reduction budget centre through an enhanced Operation and Maintenance (O&M) strategy. In the first place, a flexible framework to be applicable on complex system level of machinery can be introduced towards ship maintenance scheduling of systems, subsystems and components.;This holistic inspection and maintenance notion should be implemented by integrating different strategies, methodologies, technologies and tools, suitably selected by fulfilling the requirements of the selected ship systems. In this thesis, an innovative maintenance strategy for ship machinery is proposed, namely the Probabilistic Machinery Reliability Assessment (PMRA) strategy focusing towards the reliability and safety enhancement of main systems, subsystems and maintainable units and components.;In this respect, the combination of a data mining method (k-means), the manufacturer safety aspects, the dynamic state modelling (Markov Chains), the probabilistic predictive reliability assessment (Bayesian Belief Networks) and the qualitative decision making (Failure Modes and Effects Analysis) is employed encompassing the benefits of qualitative and quantitative reliability assessment. PMRA has been clearly demonstrated in two case studies applied on offshore platform oil and gas and selected ship machinery.;The results are used to identify the most unreliability systems, subsystems and components, while advising suitable practical inspection and maintenance activities. The proposed PMRA strategy is also tested in a flexible sensitivity analysis scheme.There is no doubt that recent years, maritime industry is moving forward to novel and sophisticated inspection and maintenance practices. Nowadays maintenance is encountered as an operational method, which can be employed both as a profit generating process and a cost reduction budget centre through an enhanced Operation and Maintenance (O&M) strategy. In the first place, a flexible framework to be applicable on complex system level of machinery can be introduced towards ship maintenance scheduling of systems, subsystems and components.;This holistic inspection and maintenance notion should be implemented by integrating different strategies, methodologies, technologies and tools, suitably selected by fulfilling the requirements of the selected ship systems. In this thesis, an innovative maintenance strategy for ship machinery is proposed, namely the Probabilistic Machinery Reliability Assessment (PMRA) strategy focusing towards the reliability and safety enhancement of main systems, subsystems and maintainable units and components.;In this respect, the combination of a data mining method (k-means), the manufacturer safety aspects, the dynamic state modelling (Markov Chains), the probabilistic predictive reliability assessment (Bayesian Belief Networks) and the qualitative decision making (Failure Modes and Effects Analysis) is employed encompassing the benefits of qualitative and quantitative reliability assessment. PMRA has been clearly demonstrated in two case studies applied on offshore platform oil and gas and selected ship machinery.;The results are used to identify the most unreliability systems, subsystems and components, while advising suitable practical inspection and maintenance activities. The proposed PMRA strategy is also tested in a flexible sensitivity analysis scheme