Performance evaluation of a two-machine line with a finite buffer and condition-based maintenance

Fitouhi, Mohamed-Chahir; Nourelfath, Mustapha; Gershwin, Stanley B.

doi:10.1016/j.ress.2017.03.034

Cited by 53 publications

(26 citation statements)

References 36 publications

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“…Existing research of condition-based maintenance of production systems largely sets a single threshold on the state of a machine. 9–11,13 This paper proposes the maintenance policies with two-threshold and four-threshold structures, which consider the stock level in adjacent buffers. This section compares the results of the maintenance optimisation using the three policy structures.…”

Section: Numerical Studymentioning

confidence: 99%

“…Tan and Gershwin 10 analysed the steady state of a production system with two machines and one buffer by solving differential equations, where the product flow in the system was assumed to be continuous. Fitouhi et al 11 used the Markov model to estimate the performance of a two-machine and one buffer flow line system, where both the minimal repair and condition-based maintenance were considered. Gebennini and Grassi 12 developed a discrete-time discrete-state Markov model for a production system with two machines and one buffer, where the buffer bypass and buffer depended production rates were considered.…”

Section: Introductionmentioning

confidence: 99%

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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: Numerical Studymentioning

confidence: 99%

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:

View full text Add to dashboard Cite

show abstract

“…Then a Lagrangian-based heuristic procedure for the solution is proposed and discussed, which includes both minimal repair and preventive maintenance. The problem of the optimal policy for Preventive Maintenance scheduling is analyzed in Ambani et al (2010), and more recently (Fitouhi et al 2017), investigates the impact of a Condition-based Maintenance policy on the performance evaluation of a two-machine line where machines are characterized by degrading behavior, by means of an analytical model. Moreover (de Jonge et al 2017), analyzes in which cases condition-based preventive maintenance is to be preferred to time-based preventive maintenance.…”

Section: Literature Reviewmentioning

confidence: 99%

Switching- and hedging- point policy for preventive maintenance with degrading machines: application to a two-machine line

Magnanini

Tolio

2019

Flex Serv Manuf J

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Maintenance and production are frequently managed as separate activities although they do interact. Disruptive events such as machine failures may find the company unready to repair the machine immediately leading to time waste. Preventive Maintenance may be carried out and maintenance time reduced to the effective task duration, in order to prevent time waste. Companies and researchers have been focusing on policies able to mitigate the impact of Preventive Maintenance on system availability, by exploiting the knowledge about degradation profiles in machines and the joint information from the machine state and the buffer level. In this work, the mathematical proof of the optimal threshold-based control policy for Preventive Maintenance with inventory cost, maintenance cost, backlog cost is provided. The control policy is defined in terms of buffer thresholds and dependency of the thresholds on the degradation condition. The optimal control policy is proved to include a combination of switching points and hedging points, where the first ones activate the Preventive Maintenance for a given condition and the latter ones control the production rate in order to minimize the surplus. An extensive experimental campaign analyzes the impact of system parameters such as the Maintenance duration on the cost function. The results show that there exists cases in which the optimal policy is dominated by the effect of the hedging points or the switching points, alternatively. Therefore, the proposed method is used to provide suggestions to the management for operative decisions, in order to choose the policy fitting best the system.

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“…24 Ribeiro et al used a mixed integer linear programming model to jointly optimize the maintenance policy and buffer size. 25 Fitouhi et al 26 proposed a maintenance model by analyzing the trade-off between preventive maintenance and buffer size. Cheng developed a maintenance model by using buffer size K and working age T as two decision variables.…”

Section: Introductionmentioning

confidence: 99%

A Combined Maintenance Strategy Considering Spares, Buffer, and Quality

Gan

Wang

Song

2021

Proceedings of the Institution of Mechanical Engineers, Part O:

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This paper studies an innovative maintenance model for an upstream machine in a common production system. Multiple system-wise features are integrated in the model, including maintenance, spare parts, buffer inventory, and product quality. The objective is to minimize the system expected cost rate by determining the optimal inspection interval, preventive maintenance threshold, corrective maintenance threshold, reorder level of spare parts, maximum stock level of spare parts, and maximum inventory level of the buffer. In this maintenance model, both the hazard rate and the product qualification rate can trigger maintenance activities. The well-known proportional hazard model (PHM) is adopted to describe the state of the upstream machine. The effect of machine state on product quality is explicitly characterized. Due to the complexity of the mathematical model, simulation and a genetic algorithm are employed to determine the optimal solution. A case study of bearings is presented to demonstrate the performance of the proposed maintenance policy. The results show that this policy is practical and can reduce system cost significantly.

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Performance evaluation of a two-machine line with a finite buffer and condition-based maintenance

Cited by 53 publications

References 36 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

Switching- and hedging- point policy for preventive maintenance with degrading machines: application to a two-machine line

A Combined Maintenance Strategy Considering Spares, Buffer, and Quality

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