• 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.

• Proceedings of the Korean Society for Quality Management Conference
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• 1998.11a
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• pp.269-276
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• 1998

This paper proposes an opportunistic age replacement policy. The system has two types of failures. Type I failures (minor failures) are removed by minimal repairs, whereas type II failures are removed by replacements. Type I and type II failures are age-dependent. A system is replaced at type II failure (catastrophic failure) or at the opportunity after age T, whichever occurs first. The cost of the minimal repair of the system at age z depends on the random part C(z) and the deterministic part c(z). The opportunity arises according to a Poisson process, independent of failures of the component. The expected cost rate is obtained. The optimal $T^{\ast}$ which would minimize the cost rate is discussed. Various special cases are considered. Finally, a numerical example is given.

• Journal of Korean Society for Quality Management
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• v.31 no.3
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• pp.185-192
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• 2003

In this paper, the properties on the optimal replacement policies for the general failure model are developed. In the general failure model, two types of system failures may occur : one is Type I failure (minor failure) which can be removed by a minimal repair and the other, Type II failure (catastrophic failure) which can be removed only by complete repair. It is assumed that, when the unit fails, Type I failure occurs with probability 1-p and Type II failure occurs with probability p, $0\leqp\leq1$. Under the model, the system is minimally repaired for each Type I failure, and it is repaired completely at the time of the Type II failure or at its age T, whichever occurs first. We further assume that the repair times are non-negligible. It is assumed that the minimal repair times in a renewal cycle consist of a strictly increasing geometric process. Under this model, we study the properties on the optimal replacement policy minimizing the long-run average cost per unit time.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.58 no.1
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• pp.27-32
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• 2009

A technical system generally comprise a number of subsystems and components that are interconnected in such a way that the system is able to perform a set of required function. Because of the complex system structure with serial, parallel and bridged connections, some certain subsystems or components are more critical than the others. The main concern of a reliability engineer is to identify potential failures and to prevent these failures from occurring. In order to prevent fatal failures, proper inspections and maintenance actions for each component are required Considering above objectives of reliability engineers and characteristics of a practical system, several practical method for evaluating system and component reliabilities have developed namely Birnbaum's and Fussell & Vesely's measures. However there are several critical weaknesses in traditional calculation process as the target system gets larger. In this paper, a new technique for calculating component's structural importance is proposed and compared to Birnbaum's with representative system examples (serial, parallel. k out of n, and bridge type).

• The Journal of the Korean dental association
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• v.51 no.11
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• pp.604-609
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• 2013

Crown fractures are relatively common trauma to anterior teeth, and should be restored immediately in most cases. For those who suffer from unfortunate traumatic episode, the best treatment option should be minimally invasive approach. In the presence of fractured tooth fragment, reattachment procedure creates positive emotional response in the patient and simplifies the procedure and maintenance of the patient's original tooth anatomy and occlusion. Without fractured tooth fragment, next conservative option could be direct composite restoration which is based on minimal invasion concept. This article proposes simple and very conservative techniques that anyone can do in daily practice.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.47
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• pp.47-55
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• 1998

This paper proposes a maintenance model considering the Inherent availability of certain requirement and two types of failures, repairable or irrepairable. In this model, the system is replaced in time when it doesn't meet the inherent availability requirement despite of all repairable failures; Otherwise it is replaced by the first irrepairable failure. Assuming that the j-th failure is repairable with probability ${\alpha}_j$, minimal repairs are performed for repairable failures between replacements. We drive the expected cost rate through the application of NHPP(Non-Homogeneous Poisson Process) in order to determine the optimal number $n^*$. The model includes some previous studies as special cases.

• Journal of the Korean Data and Information Science Society
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• v.17 no.3
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• pp.743-752
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• 2006

This paper considers a Bayesian approach to replacement policy model with minimal repair. We use the criterion based on the expected cost and the expected downtime to determine the optimal replacement period. To do so, we obtain the expected cost rate per unit time and the expected downtime per unit time, respectively. When the failure time is Weibull distribution with uncertain parameters, a Bayesian approach is established to formally express and update the uncertain parameters for determining an optimal maintenance policy. Especially, the overall value function suggested by Jiagn and Ji(2002) is applied to obtain the optimal replacement period. The numerical examples are presented for illustrative purpose.

• International Journal of Reliability and Applications
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• v.14 no.2
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• pp.55-70
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• 2013

This paper deals with the Bayesian analysis of the failure data of a repairable mechanical system subject to minimal repairs and periodic overhauls. The effect of overhauls on the reliability of the system is modeled by a proportional age reduction model and the failure process between two successive overhauls is assumed to be 2-parameter Engelhardt-Bain process (2-EBP). Power Law Process (PLP) model has a disadvantage which 2-EBP can overcome. On the basis of the observed data and of a number of suitable prior densities, point and interval estimation of model parameters, as well as quantities of relevant interest are found. Also hypothesis tests on the effectiveness of performed overhauls have been developed using Bayes factor. Sensitivity analysis of improvement parameter is carried out. Finally, a numerical application is used to illustrate the proposed method.

• Journal of Korean Society for Quality Management
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• v.21 no.2
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• pp.109-120
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• 1993

Most systems are composed of components which have different failure chracteristics. Since the failure characteristics of components is different, it is rational and reasonable to establish a maintenance model to be considered repair and replacement policies which are proper to failure characteristics of these components. This paper proposes the age replacement time for a system composed of components which have different failure characteristics. In this model, it is assumed that a system is composed of a critical failure component, a major failure component, minor failure component. If any failure occurs to critical component before its age replacement time, the system should be replaced. If any failure does not occur until its age replacement time, preventive replacement should be performed at age replacement time T. Major component is minimal repaired if any failure occurs during operation. Minor component should be replaced as soon as failure is found. This paper determines the optimal replacement time of the system which minimize, total maintenance cost and initial stock Quantity of minor component within this optimal replacement time. Numerical example illustrates these results.

• 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.