• Journal of Korean Society of Industrial and Systems Engineering
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• v.29 no.3
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• pp.135-142
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• 2006

Engineers are always concerned with life cycle costs for making important economic decisions through engineering action like reliability of products. Decisions during the reliability growth development of products involve trade-offs between invested costs and its returns. In order to find minimal LCC containing the reliability improvement cost, production cost, repair and replacement costs, and holding cost of spare parts for failure items we suggest in this paper relationship between development cost and sustaining cost in values of growth parameter $\beta$ of AMSAA model. This model is applied to the reliability growth program based on AMSAA model during R&D phase, the warranty activities of items and the block replacement policy for maintenance of items in avionic equipment.

• Journal of the Korea Institute of Building Construction
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• v.5 no.1 s.15
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• pp.97-103
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• 2005

Building costs means capital costs which include cost of land, costs of acquiring and preparing the site, construction costs, professional fees, furnishings, cost of financing the project. and cost of management required to run and maintenance the building for use. There are several phases that determine the building costs : design phase, construction phase, and operation & maintenance phase. So, the cost of work could be set against the examining the full range of complexities that a building program might contain. To solve this problem, it needs to compute building cost systematically. This is still in the development stage, awaiting the organization of rational cost data base. The method of cost saving by cost control could be constituted by detailed knowledge of building costs for all possible combinations of components and subsystems that can be assembled into integration model of cost factor on each phase of project development. The model of cost saving in each building phase is available for procedures of cost control of building systems.

• Journal of KIISE:Software and Applications
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• v.31 no.5
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• pp.555-562
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• 2004

Software industry has put more emphasis on maintenance and enhancement work than on the new development. The existing effort estimation models can still be applied to maintenance projects, though modifications are needed. This paper suggests a way to estimate the size of a maintenance project from the regression analysis of ISBSG's benchmarking data. First of all, among the 3 elements(addition, modification and deletion of the program) which influences the software cost, we selected and classified 4 groups from a total of 8 which shows actual maintenance cost from ISBSG's data. Moreover, we developed statistical model and a model which uses RBF(Radial Basis Function) Network and after evaluating each functions we concluded that the RBF Network is superior to the statistical model.

• Proceedings of the Korean Reliability Society Conference
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• 2005.06a
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• pp.115-120
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• 2005

This paper introduces models for preventive maintenance policies and considers periodic preventive maintenance policy with minimal repair when the failure of system occurs. It is assumed that minimal repairs do not change the failure rate of the system. The failure rate under prevention maintenance received an effect by a previously prevention maintenance and the slope of failure rate increases the model where it considered. Also the start point of failure rate under prevention maintenance considers the degradation of system and that it increases quotient, it assumed. Per unit time it bought an expectation cost from under this prevention maintenance policy. We obtain the optimal period time and the number for the periodic preventive maintenance by using Nakagawa's Algorithm, which minimizes the expected cost rate per unit time. Finally, it suppose that the failure time of a system has a Weibull distribution as an example and we obtain an expected cost rate per unit time the optimal period time and the number when cost of replacement and cost of minimal repair change.

• International Journal of Reliability and Applications
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• v.12 no.1
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• pp.41-48
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• 2011

This paper considers the maintenance model suggested by Jung and Park (2010) to adopt the Bayesian approach and obtain an optimal replacement policy following the expiration of NFRRW. As the criteria to determine the optimal maintenance period, we use the expected cost during the life cycle of the system. When the failure times are assumed to follow a Weibull distribution with unknown parameters, we propose an optimal maintenance policy based on the Bayesian approach. Also, we describe the revision of uncertainty about parameters in the light of data observed. Some numerical examples are presented for illustrative purpose.

• Proceedings of the KSR Conference
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• 2007.05a
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• pp.735-742
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• 2007

To get competitiveness in international markets, it is essential to provide low acquisition, maintenance and operation cost with high reliability, availability and maintainability. It can be achieved by lowering development cost, making proper maintenance planning and scheduling strategies, allocating man power and logistic cost properly. In this paper, we introduces the research on making a model for estimating the life cycle cost of newly developing magnetic levitation train system in Korea. To develop a proper life cycle cost model, we broadly analyzed specs and standards and compared the life cycle cost model developed in other country. Finally, we suggests strategies to develop an unique model for the magnetic levitation train system developing in Korea.

• 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 Applied Reliability
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• v.14 no.2
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• pp.122-128
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• 2014

In this paper, we consider the periodic preventive maintenance model for a repairable system following the expiration of extended warranty under replacement-repair warranty. Under the replacement-repair warranty, the failed system is replaced or minimally repaired by the manufacturer at no cost to the user. Also, under extended warranty, the failed system is minimally repaired by the manufacturer at no cost to the user during the original extended warranty period. As a criterion of the optimality, we utilize the expected cost rate per unit time during the life cycle from the user's perspective. And then we determine the optimal preventive maintenance period and the optimal preventive maintenance number by minimizing the expected cost rate per unit time. Finally, the optimal periodic preventive maintenance policy is given for Weibull distribution case.

• Communications for Statistical Applications and Methods
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• v.17 no.6
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• pp.865-877
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• 2010

This paper considers the periodic preventive maintenance model for a repairable system following warranty expiration. We consider three types of warranty policies: free repair warranty, pro-rata repair warranty, and combination repair warranty. Under these preventive maintenance models, we derive the expressions for the expected cycle length, the total expected cost, and the expected cost rate per unit time. In addition, we explain the optimal preventive maintenance period and the optimal preventive maintenance number by minimizing the expected cost rate per unit time. Finally, the optimal periodic preventive maintenance policy is given for a Weibull distribution case.

• Journal of the military operations research society of Korea
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• v.28 no.1
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• pp.97-114
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• 2002

An estimation of economic life for a new weapon system is a critical issue in aquisition process. In general a life cycle cost consists of, development cost, aquisition cost, and maintenance cost. These costs are not identified and obtained in the beginning of the aquisition process. This paper deals with an economic life for KlAl tank which is being deployed recently, using PRICE model. In order to estimate an KlAl economic life, we use equivalent annual cost method which is sum of capital recovering with return and equivalent O&M cost method. This method determines an economic life by minimizing annual investment cost and operation and maintenance cost. In this paper, an aquisition cost of KlAl is obtained from PRICE H and O&M cost from PRICE HL model. We obtained various results depending upon production quantity. An economic life for KlAl is estimated 18 years when 300 tanks are produced.