Reliability and covariance estimation of weighted k-out-of-n multi-state systems

Wang, Yong; Li, Lin; Huang, Shuhong; Chang, Qing

doi:10.1016/j.ejor.2012.02.037

Cited by 46 publications

(20 citation statements)

References 23 publications

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“…RCM is a systematic decision making process to keep balance between preventive and corrective maintenance actions and select cost-effective maintenance plans in order to improve the reliability [2]. Also, reliability has been widely known as a critical criterion for system design, operation, and maintenance [3]. System dynamics approach is used in different areas such as social science, economics, politics, engineering, manufacturing, and management to simulate the system interactions.…”

Section: Introductionmentioning

confidence: 99%

Reliability centered maintenance using system dynamics approach

Khorshidi

Gunawan

Ibrahim

2015

2015 IEEE International Conference on Industrial Technology (ICIT)

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This paper presents a system dynamic modeling technique for reliability centered maintenance (RCM). It provides a simulation model to analyze the impact of maintenance strategies such as preventive and corrective maintenance on system availability. Also, maintenance cost is associated with the model to have an optimization view for a manufacturing system. As a result, the optimal decisions can be made based on the results of the model. In addition, sensitivity analysis has been conducted for various parameters in the simulation model. The results were compared and discussed for various conditions.

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Section: Introductionmentioning

confidence: 99%

Reliability centered maintenance using system dynamics approach

Khorshidi

Gunawan

Ibrahim

2015

2015 IEEE International Conference on Industrial Technology (ICIT)

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“…It is possible to perform throughput modeling of more complex production systems with closed-loop structures [31], assembly/disassembly features [32], and more complex material handling systems [27]. It is also worth exploring the extensibility of the proposed method to the cases involving stochastic or uncertain machine reliability parameters [33]- [36]. Further research work may also involve expanding the proposed method for joint production and energy consumption modeling and management of manufacturing systems [37]- [40].…”

Section: Discussionmentioning

confidence: 99%

A Novel Modeling Method for Both Steady-State and Transient Analyses of Serial Bernoulli Production Systems

Wang

2015

IEEE Trans. Syst. Man Cybern, Syst.

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Conventionally, production system modeling (PSM) has been conducted for the purpose of steady-state analysis, which only facilitates characterizing the long-term performance of production systems. More recently, there has been a rising concern regarding analyzing production system transients, which depict the system behavior before reaching the steady state. Transients are generally undesirable because the performance measures can be quite different from those of the steady state, and such differences will cause substantial production loss. Compared to the rich knowledge on steady-state analysis of production systems, PSM for transient performance analysis is much less studied. In this paper, a novel analytical method has been established to model the production system for both steady-state and transient analyses. This research has overcome the restrictions of existing methods on the number of machines and the capacity of buffers. That is, it has greatly advanced PSM for both steady-state and transient analyses by directly dealing with general serial production systems with multiple unreliable Bernoulli machines and finite buffer capacities. The proposed PSM is a method derived based on probability theory and fixed-point theory. The solvability of the method is proved theoretically. The transient performance metrics, such as second largest eigenvalue modulus, duration of the transients (t ITER ), settling time of workin-process (t WIP ) and production rate (t PR ), and percent loss of production (L PR ) have been investigated numerically based on the proposed PSM method. This research can serve as an atomic model for more complex optimization problems in production system design and operation.

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“…Formally, a weighted k-out-of-n system is in an operating state iff the total weight of working components is at least k. Clearly, this system reduces to the usual k-out-of-n model if each component has a weight of one. The weighted k-out-of-n systems have been studied in [10][11][12][13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Multivariate copula based dynamic reliability modeling with application to weighted-k-out-of-n systems of dependent components

Eryılmaz

2014

Structural Safety

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Reliability and covariance estimation of weighted k-out-of-n multi-state systems

Cited by 46 publications

References 23 publications

Reliability centered maintenance using system dynamics approach

Reliability centered maintenance using system dynamics approach

A Novel Modeling Method for Both Steady-State and Transient Analyses of Serial Bernoulli Production Systems

Multivariate copula based dynamic reliability modeling with application to weighted-k-out-of-n systems of dependent components

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