A myopic policy for optimal inspection scheduling for condition based maintenance

Last-minute maintenance planning is often undesirable, as it may cause downtime during operational hours, may require rescheduling of other activities, and does not allow to optimize the management of spare parts, material, and personnel. In spite of the aforementioned drawbacks of last-minute planning, most existing methods plan maintenance activities at the last minute. In this paper, we propose a new strategy for timely maintenance planning in multi-component systems. As a first step, we determine for each system component independently the most appropriate maintenance planning strategy. This way, the maintenance decisions can be tailored to the specific situations. For example, conservative maintenance decisions can be taken when the risk tolerance is low, and maintenance decisions can be made timely when we can accurately predict future degradation behavior. In the second step, we optimize the maintenance plan at the system level. Here, we account for economic and structural dependence with the aim to profit from spreading or combining various maintenance activities. The applicability of the method is demonstrated on a railway case. It is shown how the different cost functions (e.g. costs of maintenance, downtime, and failure) influence the maintenance decisions.

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“…Most of these works (e.g. [9][10][11][12][13][14]) base their maintenance decisions on just diagnostic information.…”

Section: Literature Reviewmentioning

confidence: 99%

Timely condition-based maintenance planning for multi-component systems

Verbert

Schutter

Babuška

2017

Reliability Engineering & System Safety

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“…However, in the second approach, the duration is constant, but frequency achieves by running a model considering different economic measurements. In the third approach, the duration is not constant and the frequency is not predefined but by running a model the optimal plan will be extracted [7][8][9][10]. Furthermore, all possible inspection schemes were incorporated to prevent local optimum solution and avoid unnecessary combinations [11].…”

Section: Introductionmentioning

confidence: 99%

Integrated Inspection Planning and Preventive Maintenance for a Markov Deteriorating System Under Scenario-based Demand Uncertainty

Noori

Sadegheih

Lotfi

2020

IJE

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In this paper, a single-product, single-machine system under Markovian deterioration of machine condition and demand uncertainty is studied. The objective is to find the optimal intervals for inspection and preventive maintenance activities in a condition-based maintenance planning with discrete monitoring framework. At first, a stochastic dynamic programming model whose state variable is the machine status is presented. In the first model, the demand is assumed to be deterministic and the objective is to minimize the sum of inspection, preventive maintenance, and lost sale costs. Then, in order to take the demand uncertainty into account, the extended model is formulated as a scenario-based two-stage stochastic programming one. In the second model, selecting the best inspection plan and finding the appropriate intervals for preventive maintenance are considered as the first and second stage decisions, respectively. Analyzing an illustrative example to study the effect of demand uncertainty in the problem shows that

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“…With the fast development of sensing techniques, system states can now be monitored or inspected at a much lower cost, which facilitates to characterise the deteriorating process of the system by a continuous-time stochastic model (Lam & Banjevic, 2015). For a system subject to a continuous-time degradation process, condition-based maintenance (CBM) has shown its effectiveness and predominance in preventing unexpected failures.…”

Section: Introductionmentioning

confidence: 99%