• IE interfaces
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• v.13 no.4
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• pp.680-687
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• 2000

The objectives of this research are to establish the operation scheduling and the preventive maintenance system in order to optimize the operation of mailing center. For the optimal operation scheduling of mailing process, the existing workflow of mailing process and that of required time are investigated prior to simulation modeling. The simulation experiments are conducted to increase the nextday delivery rate. The best alternative whose nextday delivery rate up to 100% is selected based the AHP(Analytic Hierarchy Process) method. The optimal work scheduling of all mailing centers are also presented. In addition, the CMMS(Computerized Maintenance Management System) for preventive maintenance is introduced for efficient operation of highly automated facilities of mailing center.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.7
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• pp.34-40
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• 2014

In this paper, we want to know the optimal replacement cycle(time) for this study was performed. The optimal preventive replacement age can be fond by finding the value of time that minimizes the cost function(model of Barlow and Jardine). In addition, The reliability of the relay according to the service environment were studied. The use of the exchange relay period is longer, and maintenance cost rate(per hour) may increase, and also the reliability may cause a decline. In addition, considering the preventive maintenance and purchase order, a representative relay(RAX-L440-A type) life was calculated.

• Journal of Wind Energy
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• v.14 no.3
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• pp.61-68
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• 2023

This paper aims to perform optimal operation and maintenance with an integrated monitoring system for offshore wind platforms. Based on the wind direction and wind speed data of existing wind farms, a monitoring system was established along with weather and weather data to maximize the operational efficiency of wind farms. Compared to wind power on land, offshore wind power is difficult to maintain due to weather, logistics and geographical limitations. Therefore, economic analysis of actual operation and maintenance is essential for large-scale offshore wind farms. In this paper, the availability of offshore wind farms was analyzed by using personnel resources, parts inventory, Crew Transfer Vessel (CTV) and Specialized service Operation Vessel (SOV) etc. before the actual operation and maintenance of wind farms. A comparative analysis was conducted to determine the optimum operating efficiency and economical maintenance costs.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.28 no.4
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• pp.191-201
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• 2016

A stochastic process has been used to develop a condition-based model for preventive maintenance of armor units of rubble-mound breakwaters that can make a decision the optimal interval at which some repair actions should be performed under the perfect maintenance. The proposed cost model in this paper based on renewal reward process can take account of the interest rate, also consider the unplanned maintenance cost which has been treated like a constant in the previous studies to be a time-dependent random variable. A function for the unplanned maintenance cost has been mathematically proposed so that the cumulative damage, serviceability limit and importance of structure can be taken into account, by which a age-based maintenance can be extended to a condition-based maintenance straightforwardly. The coefficients involved in the function can also be properly estimated using a method expressed in this paper. Two stochastic processes, Wiener process and gamma process have been applied to armor stones of rubble-mound breakwaters. By evaluating the expected total cost rate as a function of time for various serviceability limits, interest rates and importances of structure, the optimal period of preventive maintenance can easily determined through the minimization of the expected total cost rate. For a fixed serviceability limit, it shows that the optimal period has been delayed while the interest rate increases, so that the expected total cost rate has become lower. In addition, the gamma process tends to estimate the optimal period more conservatively than the Wiener process. Finally, it is found that the more crucial the level of importance of structure becomes, the more often preventive maintenances should be carried out.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.4
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• pp.487-493
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• 2007

In this paper, we deal with an optimal software-release problem of determining the time to stop testing and release the software system to the user. The optimal release time problem is considered from maintenance like the periodic distribution of service packs and the unpredictable distribution of patches after the release. Moreover, the environment of software error-detection during operation differs from the environment during testing. This paper proposes the software reliability growth model which incorporates periodic service packs, unpredictable patches and operational environment. Based on the proposed model, we derive optimal release time to minimize total cost composed of fixing an error, testing and maintenance. Using numerical examples, optimal release time is determined and illustrated.

• International Journal of Reliability and Applications
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• v.11 no.2
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• pp.69-87
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• 2010

The optimal replacement problem was investigated for a multi-state deteriorated system for which the true internal state cannot be observed directly except when the system breaks down completely. The internal state was assumed to be monitored incompletely by a monitor that gives information related to the true state of the system. The problem was formulated as a partially observable Markov decision process. The optimal procedure was found to be a monotone procedure with respect to stochastic increasing ordering of the state probability vectors under some assumptions. Limiting the optimal procedure to a monotone procedure would greatly reduce the tremendous amount of calculation time required to find the optimal procedure.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.5
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• pp.2724-2731
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• 2014

As the future national defense plan of government focus on advanced weapon system, military maintenance facility becomes more important. However, military maintenance facility has been managed by director's experience and simple mathematical calculation until now. Thus, the optimization for the management of military maintenance facility is suggested by more scientistic and logical methods in this study. The study follows the procedure below. First, simulation is designed according to the analysis of military maintenance facility. Second, independent variable and dependent variable are defined for optimization. Independent Variable includes the number of maintenance machine, transportation machine, worker in the details of military maintenance facility operation, and dependent variable involves total maintenance time affected by independent variable. Third, warmup analysis is performed to get warmup period, based on the simulation model. Fourth, the optimal combination is computed with evolution strategy, meta-heuristic, to enhance military maintenance management. By the optimal combination, the management of military maintenance facility can gain the biggest effect against the limited cost. In the future, the multipurpose study, to analyze the military maintenance facility covering various weapon system equipments, will be performed.

• Communications for Statistical Applications and Methods
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• v.15 no.1
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• pp.77-86
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• 2008

This paper develops the optimal periodic preventive maintenance policy following the expiration of non-renewing warranty. We assume that Wu and Clements-Croome's (2005) periodic PM model with random maintenance quality is utilized to maintain the system after the non-renewing warranty is expired. Given the cost structure to the user during the cycle of the product, we drive the expressions for the expected cost rate per unit time. Also, we obtain the optimal number and the optimal period by minimizing the expected cost rate per unit time. The numerical examples are presented for illustrative purpose.

• Industrial Engineering and Management Systems
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• v.8 no.4
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• pp.221-227
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• 2009

There are customer services jointly provided by two facilities so that each customer will complete the course made up of both facilities' sub-services. The two facilities are assumed invested respectively by an infrastructure owner and one subordinate facility owner, whose partnership is built on their capital investments. This paper presents a mathematical model of Stackelberg competition between the two facility owners to derive their optimal Nash equilibrium. In this study, each facility owner's profit is consisted of fixed revenue fractions of sold services, operating costs (including depreciation cost) and maintenance costs of her facility. The maintenance costs of one facility are incurred both by failures and deterioration due to usage. Moreover, for both facilities, failures are rectified immediately by minimal repairs and preventive maintenance is carried out at a fixed time epoch. Additional assumptions are also employed to develop the model such as customer arrivals are manipulated to follow a Poisson process, and each facility's lifetime is independently Weibull-distributed. The Stackelberg game proceeds as follows. At the first stage of decision making process, the infrastructure owner (acting as a leader) decides the allocation of revenue shares based on her self-interest. After observing the allocation of revenue shares, the subordinate facility owner determines her own optimal price of services. This paper investigates actions and reactions of the two partners in the system. Then analytical conditions are proposed to achieve a unique optimal Nash equilibrium. Finally, some suggestions for further research are discussed.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.3-10
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• 2022

An estimated investment gap of $176 billion needs to be filled over the next ten years to improve America's inland waterway transportation systems. Many of these infrastructure systems are now beyond their original 50-year design life and are often behind in maintenance due to funding constraints. Therefore, long-term maintenance strategies (i.e., asset management (AM) strategies) are needed to optimize investments across these waterway systems to improve their condition. Two common AM strategies include policy-driven maintenance and performance-driven maintenance. Currently, limited research exists on selecting the optimal AM approach for managing inland waterway transportation assets. Therefore, the goal of this study is to provide a decision model that can be used to select the optimal alternative between the two AM approaches by considering key uncertainties such as asset condition, asset test results, and asset failure. We achieve this goal by addressing the decision problem as a single-criterion problem, which calculates each alternative's expected value and certain equivalence using allocated monetary values to determine the recommended alternative for optimally maintaining navigable waterways. The decision model considers estimated and predicted values based on the current state of the infrastructure. This research concludes that the performance-based approach is the optimal alternative based on the expected value obtained from the analysis. This research sets the stage for further studies on fiscal constraints that will effectively optimize these assets condition.