Probabilistic method for planning of maintenance activities of substation components

Mijailović, Vladica

doi:10.1016/s0378-7796(02)00148-7

Cited by 37 publications

(24 citation statements)

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“…In age-dependent PM policy, a unit is preventively maintained at predetermined age T, or repaired at failure, whichever comes first ( [24], [25]). Barlow and Hunter [17] considered age-dependent maintenance policy for both simple and complex systems.…”

Section: Reliability Based Maintenancementioning

confidence: 99%

Joint Maintenance and Production Operations Decision Making in Flexible Manufacturing Systems

Celen

Djurdjanović

2012

ASME 2012 International Manufacturing Science and Engineering Conference

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In highly flexible and integrated manufacturing systems such as those in semiconductor manufacturing, there exist strong dynamic interactions between the equipment condition, operations executed on the equipment and the resulting product quality. These interactions necessitate a methodology that integrates the decisions of maintenance scheduling and production operations. Currently, maintenance and production operations decision-making are two decoupled processes. In this paper we aim to devise an integrated decision making policy for maintenance scheduling and production sequencing with the objective of maximizing an adaptive profit function, while taking into account operation-dependent degradation models and a production target. In order to obtain the optimal decision policy, a metaheuristic method based on the results of discrete-event simulations of the target manufacturing system is used. The new approach is demonstrated in simulations of a generic cluster tool routinely used in semiconductor manufacturing. The results show that jointly making maintenance and production sequencing decisions consistently outperforms the current practice of making these decisions separately.

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Section: Reliability Based Maintenancementioning

confidence: 99%

Joint Maintenance and Production Operations Decision Making in Flexible Manufacturing Systems

Celen

Djurdjanović

2012

ASME 2012 International Manufacturing Science and Engineering Conference

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“…The literature review shows that the impact of maintenance parameters such as reliability and availability has been investigated in a few researches [5,[12][13][14]23,36]. While former studies considered only a few features, this study investigates the influence of more parameters on improving decision making process in maintenance problems.…”

Section: Introductionmentioning

confidence: 99%

An Integrated Multi-Criteria Computer Simulation-AHP-TOPSIS Approach for Optimum Maintenance Planning by Incorporating Operator Error and Learning Effects

et al. 2016

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The objective of this study is to optimize maintenance activities in a production system by incorporating cost and reliability. An integrated multi-criteria approach is presented to optimize maintenance planning and also define its policies. Modelling maintenance activities is usually nonlinear and complex since it includes various parameters. Therefore, a simulation optimization approach is presented to handle such complexities. Production and maintenance functions are estimated by means of historical data. In this study, maintenance activities with different scenarios along with probability of human error and learning effects are discussed. The scenarios are generated from a combination of inputs such as time between preventive maintenance, number of operators and skills. Different outputs such as reliability, machine availability, human errors and cost are obtained from these scenarios. The outputs are analysed to reach the optimized scenario by using an integrated analytical hierarchy process (AHP) and techniques for order preference by similarity to ideal solution (TOPSIS) method. The applicability of this approach is shown in an actual production line with four series machines. The results of this study can be helpful for decision makers to choose the best policy of maintenance planning. This is one of the first studies that optimize reliability and human cost by considering human error and learning effects through an integrated simulation, AHP and TOPSIS approach. Keywords

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“…In response to these, a mathematical model is required to quantify the procedure of wear‐out. A considerable amount of literature has been published on the quantification of deterioration process, inspections, and maintenance of power components …”

Section: Introductionmentioning

confidence: 99%

Aging failure model of circuit breakers equipped with condition monitoring systems

Razi-Kazemi

Lehtonen

2017

Int Trans Electr Energ Syst

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Summary Lifetime management of circuit breakers (CBs) compared with the other components in power system is dependent not only on the natural age but also on the number of operation, applications, and maintenance scheduling. In addition, condition‐monitoring systems (CMSs) are widely used to extend lifetime and improve the quality of maintenance. However, the employing CMSs for CBs are faced with economical and technical challenges. This paper presents a new probabilistic aging failure model for CBs equipped with CMS. The proposed model improves the conventional approach for the assessment of efficiency of maintenance strategies using available filed data and coupling some weighting factors. The model is based on the state diagram along with Monte Carlo simulations to provide more flexibility in quantification of practical concerns. The model helps us to compare all maintenance strategies within 1 framework to select the best policy with respect to working situation of CBs. The approach has been compared and verified with the conventional aging model. Moreover, it is numerically applied to 2 common types of CBs, that is, SF6 and minimum oil based on the field data to reveal the results of considering the real aging and dynamic behavior of CBs on cost/benefits of maintenance policies. The results of applying the proposed approach to CBs indicate that ignoring the realistic situation of CBs results in a significant underestimation or overestimation of reliability and consequently making a wrong decision on installation of CMS or even in selection of the optimum inspection time.

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Probabilistic method for planning of maintenance activities of substation components

Cited by 37 publications

References 1 publication

Joint Maintenance and Production Operations Decision Making in Flexible Manufacturing Systems

Joint Maintenance and Production Operations Decision Making in Flexible Manufacturing Systems

An Integrated Multi-Criteria Computer Simulation-AHP-TOPSIS Approach for Optimum Maintenance Planning by Incorporating Operator Error and Learning Effects

Aging failure model of circuit breakers equipped with condition monitoring systems

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