Optimal maintenance of a series production system with two multi-component subsystems and an intermediate buffer

Zhou, Yifan; Zhang, Zhisheng

doi:10.17531/ein.2015.2.20

Cited by 7 publications

(3 citation statements)

References 23 publications

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“…The strategy structure of the preventive maintenance and the overhaul under different system parameters were demonstrated in the numerical study. Zhou et al 8 optimised the maintenance of a series-parallel system with one buffer and pointed that the optimal maintenance policy cannot be described by a small number of thresholds on the state of machines. The above cited papers mainly focused on the characteristics of the optimal maintenance policy for series flow line systems with one buffer.…”

Section: Introductionmentioning

confidence: 99%

Maintenance policy structure investigation and optimisation of a complex production system with intermediate buffers

Zhou

Yuan

Lin

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part O:

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Existing research about the maintenance optimisation of production systems with intermediate buffers largely assumed a series system structure. However, practical production systems often contain subsystems of ring structures, for example, rework and feedforward. The maintenance optimisation of these complex systems is difficult due to the complicated structure of maintenance policies and the large search space for optimisation. This paper proves the control limit property of the optimal condition-based maintenance policy. Based on the control limit property, approximate policy structures that incur a smaller policy space are proposed. Because the state space of a production system is often large, the objective function of the maintenance optimisation cannot be evaluated analytically. Consequently, a stochastic branch and bound (SB&B) algorithm embedding a sequential simulation procedure is proposed to determine a cost-efficient condition-based maintenance policy. Numerical studies show that the proposed maintenance policy structures can deliver a cost-efficient maintenance policy, and the performance of the SB&B algorithm is enhanced by the inclusion of a sequential simulation procedure.

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Section: Introductionmentioning

confidence: 99%

Maintenance policy structure investigation and optimisation of a complex production system with intermediate buffers

Zhou

Yuan

Lin

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part O:

Self Cite

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“…Karamatsoukis and Kyriakidis addressed the possibility of a control-limit structure when buffer is considered after the maintenance. Their model includes the effects of variation of buffer size, buffer allocation and buffer content for optimizing the minimum average cost. , Zhou and Zhang formulated a generalized minimum residual method for optimizing the intermediate buffer capacity and maintenance in series-parallel production systems. They considered an optimal maintenance strategy structure for obtaining the optimal solution.…”

Section: Introductionmentioning

confidence: 99%

Integrated Scheduling of Production and Maintenance for Continuous Plants: Conditional Sequencing and Approximate Modeling of Storage

Omar

Shaik

2019

Ind. Eng. Chem. Res.

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In this study, we present extensions of earlier models for integrated scheduling of optimal production and planned maintenance for continuous and semicontinuous plants to account for different storage requirements. For handling finite storage, we propose approximate modeling of storage (without loss of generality) based on conditional sequencing without considering storage as a separate task. For dedicated storage tanks, when the "total amount to be stored" at an event is within the storage capacity, then we model an approximation of the amount stored. The conditional alignment of consumption and production tasks is extended for handling different storage policies. These features lead to reduction in the number of events. Two different models, based on task-specific and unit-specific timing variables, are proposed for handling finite intermediate storage (FIS), no intermediate storage (NIS), and zero wait (ZW) policies by modifying different constraints in the earlier models. The proposed models are presented for two cases based on the delivery of products and intermediates (1) as and when required and (2) at the end of the time horizon. The concept of planned maintenance is simultaneously incorporated with inventory management and optimal production. The proposed models are solved on different case studies, resulting in fewer events and better computational performance for small to medium scale problems, when compared with the literature model.

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“…High availability is becoming a must in various domains such as telecommunication networks, power plants, and industrial and manufacturing systems [5, 16,27]. During the past years, many efforts have been made to improve system availability.…”

Section: Introductionmentioning

confidence: 99%

Availability analysis of series redundancy models with imperfect switchover and interrupted repairs

Shim¹,

Ryu²,

Lee³

2017

EiN

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Article citation info: Shim J, Ryu h, Lee y. Availability analysis of series redundancy models with imperfect switchover and interrupted repairs. eksploatacja i Niezawodnosc -maintenance and Reliability 2017; 19 (4): 640-649, http://dx.doi.org/10.17531/ein.2017.4.19 IntroductionThe availability of a system is defined as the probability that the system is operational at a point in time [16,25]. High availability is becoming a must in various domains such as telecommunication networks, power plants, and industrial and manufacturing systems [5, 16,27]. During the past years, many efforts have been made to improve system availability.Redundancy is a common approach to improve system availability [6]. The redundancy service can offer different levels of availability depending on its redundancy model. Availability Management Framework [16] defines the following four redundancy models: 2N, N+M, N-way, and N-way active. The 2N redundancy model ensures one standby replica for each component in active mode. The active components execute the service, while the standby components are ready to take over the active role if the active components fail. The N+M redundancy model extends the 2N redundancy by allowing more than two components to be active or standby. In the N+M redundancy, N represents the number of components in active mode and M represents the number of components in standby. The N-way redundancy model extends the N+M redundancy allowing a component to be simultaneously active and standby for different services. Lastly, the N-way active redundancy model differs from the 2N, N+M, and N-way redundancy, as it does not support standby service assignments, but allows a service to be assigned active to several components [16].The availability analysis of a redundancy model is based on analyzing the various states that the model undergoes during its lifespan [21]. The analysis mainly focuses on capturing the failures that cause the system to switch to a faulty state and the repairs that shift the system back to a healthy state [6]. Since the occurrence of failures is erratic by nature, stochastic models have been used to conduct the availability analysis [20]. Markovian models have been extensively used for this purpose because of their expressiveness and their capability of capturing the complexity of real systems [1,[23][24][25]. One of the major problems of using Markovian models is that a large number of states are required to represent the model accurately [1]. As an alternative, Kanso et al. [6] various redundancy models and evaluated the availability by using the Stochastic Petri Net Package (SPNP). Kim et al. [9] analyzed the networking service availability of 2N redundancy model with nonstop forwarding by using the SPNP. The analytic-numeric methods of SPNP provide the capabilities of solving the Markovian SRNs but fail for non-Markovian SRNs. Actually there is no reason to assume Markov property in modeling of repairable systems [11]. Recently, modeling and analysis of repairable systems with general rep...

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Optimal maintenance of a series production system with two multi-component subsystems and an intermediate buffer

Abstract: Optymalna strategia utrzymania ruchu dla seryjnegO systemu prOdukcji złOżOnegO z dwóch pOdsystemów wielOskładnikOwych Oraz bufOru pOśredniegO

Cited by 7 publications

References 23 publications

Maintenance policy structure investigation and optimisation of a complex production system with intermediate buffers

Maintenance policy structure investigation and optimisation of a complex production system with intermediate buffers

Integrated Scheduling of Production and Maintenance for Continuous Plants: Conditional Sequencing and Approximate Modeling of Storage

Availability analysis of series redundancy models with imperfect switchover and interrupted repairs

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