Modelling multicomponent systems to quantify reliability centred maintenance strategies

Zille, Valérie; Bérenguer, Christophe; Grall, Antoine; Despujols, Antoine

doi:10.1177/1748006x11402269

Cited by 18 publications

(18 citation statements)

References 31 publications

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“…30,44 Thus, in order to accurately evaluate the different maintenance strategies and find optimal solutions, most of the problem has been firstly analytically derived, and secondly implemented in simulation techniques, as commonly done in other researches. 31,44,47 Particularly, an agent-based simulation has been modelled due to its suitability to handle engineering problems with multi-agent systems, 48 such as the wind energy sector. The simulation process modelled can be summarised in six main steps (see Figure 5).…”

Section: Lcc and Lp Analysismentioning

confidence: 99%

After-sales services optimisation through dynamic opportunistic maintenance: a wind energy case study

Erguido

Crespo

Castellano

et al. 2018

Proceedings of the Institution of Mechanical Engineers, Part O:

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After-sales maintenance services can be a very profitable source of incomes for original equipment manufacturers (OEM) due to the increasing interest of assets' users on performance-based contracts. However, when it concerns the product value-adding process, OEM have traditionally been more focused on improving their production processes, rather than on complementing their products by offering after-sales services; consequently leading to difficulties in offering them efficiently. Furthermore, both due to the high uncertainty of the assets' behaviour and the inherent challenges of managing the maintenance process (e.g. maintenance strategy to be followed or resources to be deployed), it is complex to make business out of the provision of after-sales services. With the aim of helping the business and maintenance decision makers at this point, this paper proposes a framework for optimising the incomes of after-sales maintenance services through: 1) implementing advanced multi-objective opportunistic maintenance strategies that sistematically consider the assets' operational context in order to perform preventive maintenance during most favourable conditions, 2) considering the specific OEMs' and users' needs, and 3) assessing both internal and external uncertainties that might condition the after-sales services' success. The developed case study for the wind energy sector demonstrates the suitability of the presented framework for optimising the after-sales services.

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Section: Lcc and Lp Analysismentioning

confidence: 99%

After-sales services optimisation through dynamic opportunistic maintenance: a wind energy case study

Erguido

Crespo

Castellano

et al. 2018

Proceedings of the Institution of Mechanical Engineers, Part O:

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“…To overcome this limitation, the MC method can be better used with other modeling tools, such as FT [25][26][27] and Petri nets. 28,29 According to the extant research on MSS, system state is typically defined as the output of the structure function from the given state vector. Furthermore, the state vector consists of all component states, with each component state represented by natural numbers.…”

Section: Introductionmentioning

confidence: 99%

New method for multi-state system reliability analysis based on linear algebraic representation

Liu

Chen

Yang

2015

Proceedings of the Institution of Mechanical Engineers, Part O:

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Multi-state system is a certain complex system with failure criteria that are not limited to ''normal or failure.'' During the life cycle, both the system and each component inside have different states at any time point. State transition of the whole system depends on the structure function while that of any component has a certain mechanism. To directly express state transition processes of the whole system and all components, we develop a linear algebraic representation method. Based on this method, dynamic transition can be expressed by mathematic equations, in which information of both system structure function and components transition mechanism is embedded. Furthermore, the extended multi-state dynamic fault tree is introduced to multi-state system modeling. By means of the proposed linear algebraic representation, standard operating rules for both static and dynamic gates are generated by introducing two variables that are used to determine whether the transition occurs and which state the output would convert into, respectively. Then, a Monte Carlo simulation coupled with the multi-state dynamic fault tree method is proposed to calculate the reliability indices of a multi-state system. The proposed method is then validated with a dynamic fault tree problem from a literature. Finally, the servo turret system is taken as an example for the application of the proposed method.Assumptions 1. Once a component begins to function, such component cannot be recovered to the completely dormant state; meanwhile, the scrap component cannot be restored to a working stage. 2. Excluding maintenance, state transitions of components are always from a better to a worse state because of spontaneous or triggered behavior; maintenance is not considered in this study. 3. The state transition of either the whole system or a component is instantaneous with no duration, which can be depicted as state(t À i ) ! state(t + i ). 4. The total numbers of discrete states of all events in the multi-state dynamic fault tree are identical and are denoted by n. 5. When the system starts working, spare parts can only exist in SPARE gates.

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“…developed a modularised PN model for manufacturing production line systems integrating corrective and preventative maintenance. Zille et al . used PNs to assess the performance of multicomponent systems maintained by complex maintenance strategies.…”

Section: Introductionmentioning

confidence: 99%

Use of Petri Nets to Model the Maintenance of Wind Turbines

Leigh

Dunnett

2014

Qual. Reliab. Engng. Int.

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With large expansion plans for the offshore wind turbine industry, there has never been a greater need for effective operations and maintenance. The two main problems with the current operations and maintenance of an offshore wind turbine are the cost and availability. In this work, a simulation model has been produced of the maintenance process for a wind turbine with the aim of developing a procedure that can be used to optimise the process. This initial model considers three types of maintenance—periodic, conditional and corrective—and also considers the weather in order to determine the accessibility of the turbine. Petri nets have been designed to simulate each type of maintenance and weather conditions. It has been found that Petri nets are a very good method to model the maintenance process because of their dynamic modelling and adaptability and their ability to test optimisation techniques. Because of their versatility, Petri net models are developed for both system hardware and the maintenance processes, and these are combined in an efficient and concise manner. Copyright © 2014 John Wiley & Sons, Ltd.

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Modelling multicomponent systems to quantify reliability centred maintenance strategies

Cited by 18 publications

References 31 publications

After-sales services optimisation through dynamic opportunistic maintenance: a wind energy case study

After-sales services optimisation through dynamic opportunistic maintenance: a wind energy case study

New method for multi-state system reliability analysis based on linear algebraic representation

Use of Petri Nets to Model the Maintenance of Wind Turbines

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