Wind Turbine Optimal Preventive Maintenance Scheduling Using Fibonacci Search and Genetic Algorithm

Maintenance scheduling is essential and crucial for wind turbines (WTs) to avoid breakdowns andreduce maintenance costs. Many maintenance models have been developed for WTs’ maintenance planning, suchas corrective, preventive, and predictive maintenance. Due to communities’ dependence on WTs for electricityneeds, preventive maintenance is the most widely used method for maintenance scheduling. The downside tousing this approach is that preventive maintenance (PM) is often done in fixed intervals, which is inefficient. In thispaper, a more detailed maintenance plan for a 2 MW WT has been developed. The paper’s focus is to minimize aWT’s maintenance cost based on a WT’s reliability model. This study uses a two-layer optimization framework:Fibonacci and genetic algorithm. The first layer in the optimization method (Fibonacci) finds the optimal numberof PM required for the system. In the second layer, the optimal times for preventative maintenance and optimalcomponents to maintain have been determined to minimize maintenance costs. The Monte Carlo simulationestimates WT component failure times using their lifetime distributions from the reliability model. The estimatedfailure times are then used to determine the overall corrective and PM costs during the system’s lifetime. Finally,an optimal PM schedule is proposed for a 2 MW WT using the presented method. The method used in this papercan be expanded to a wind farm or similar engineering systems.

Analysis of a POMDP Model for an Optimal Maintenance Problem with Multiple Imperfect Repairs

I consider a system whose deterioration follows a discrete-time and discrete-state Markov chain with an absorbing state. When the system is put into practice, I may select operation (wait), imperfect repair, or replacement at each discrete-time point. The true state of the system is not known when it is operated. Instead, the system is monitored after operation and some incomplete information concerned with the deterioration is obtained for decision making. Since there are multiple imperfect repairs, I can select one option from them when the imperfect repair is preferable to operation and replacement. To express this situation, I propose a POMDP model and theoretically investigate the structure of an optimal maintenance policy minimizing a total expected discounted cost for an unbounded horizon. Then two stochastic orders are used for the analysis of our problem.

Network-level optimization method for road network maintenance programming based on network efficiency

To maintain their capacity,transportation infrastructures are in need of regular maintenance and rehabilitation.The major challenge facing transportation engineers is the network-level policies to maintain the deteriorating roads at an acceptable level of serviceability.In this work,a quantitative transportation network efficiency measure is presented and then how to determine optimally network-level road maintenance policy depending on the road importance to the network performance has been demonstrated.The examples show that the different roads should be set different maintenance time points in terms of the retention capacities of the roads,because the different roads play different roles in network and have different important degrees to the network performance.This network-level road maintenance optimization method could not only save lots of infrastructure investments,but also ensure the service level of the existing transportation system.

Availability modelling for periodically inspected systems under mixed maintenance policies

The availability of a periodic inspection system under mixed maintenance policies is studied in this paper.To accommodate the characteristic of multiple failure modes for complex systems,the system failures can be divided into two failure modes:hard failure and soft failure.When hard failure occurs,the corresponding corrective maintenance will be performed,taking a random time under the perfect maintenance policy;in contrast,if the soft failure is found,the corresponding preventive maintenance will be performed,taking a random time under the imperfect maintenance policy.The dynamic age setback model is adopted for imperfect maintenance,which can accurately reflect the fault characteristics of the degraded system.Then an analytical model for system steady state availability and instantaneous availability are derived.Moreover,the optimal method to maximize the system steady-state availability through adjusting the inspection interval is researched.According to the above research,the optimization of system unit time cost,preventive maintenance intervals and availability is researched.Finally,the developed approach is demonstrated by a numerical example.

A Markov Model for Production and Maintenance Decision

In this paper,we consider a production machine which may fail and it is necessary to repair the machine after each failure and there are two statuses for each repair;in one case,we should replace the machine because of catastrophic failure and in the other case,only small repairs are needed.Times between failures and repair and replace times are random and demands are satisfied by inventory during repairing and replacing the machine;shortage level is limited.We model described system as a Markov chain and develop an algorithm to compute the expected number of transitions among states.