• Journal of Korean Society for Quality Management
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• v.47 no.1
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• pp.87-96
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• 2019

Purpose: The purpose of this paper is to determine an optimal production time for economic production quantity model with preventive maintenance and random defective rate as the function of a machinery deteriorates. Methods: If a machinery shifts from "in-control" state to "out-of-control" state, a proportion of defective items being produced increases. It is assumed that time to state shift is a random variable and follows an arbitrary distribution. The elapsed time until process shift decreases stochastically as a production cycle repeats and quasi-renewal process is used to implement for production facilities to deteriorate. Results: When the exponential parameter for exponential distribution increases, the optimal production time increases. When Weibull distribution is considered, the optimal production time is closely affected by the shape parameter of Weibull distribution. Conclusion: A mathematical model is suggested to find optimal production time and optimal number of production cycles and numerical examples are implemented to validate the patterns for changes of optimal times under different parameters assumptions. The real application is implemented using the proposed approach.

• Journal of Advanced Marine Engineering and Technology
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• v.24 no.2
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• pp.90-96
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• 2000

The technology of preventive maintenance and corrective maintenance is widely applied to ships in order to maintain the good voyageable condition. One of the most important fields of marine engineering is to seek the maximum availability and to solve the stochastic maintenance problem such that the cost for corrective maintenance is minimized. Accordingly, for the purpose of making the most suitable maintenance schedule which minimizes the expected cost function, this paper suggests the method to grasp the failure characteristics by the ship's maintenance data that are collected from the past. And, suggests the method to estimate the optimal maintenance interval by using the dynamic programming and the cumulative hazard rate function attained from the maintenance data.

• Journal of the Korean Data and Information Science Society
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• v.19 no.2
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• pp.587-596
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• 2008

This paper develops the optimal periodic preventive maintenance policies following the expiration of warranty: renewing warranty and non-renewing warranty. After the warranty period is expired, the system undergoes the PM periodically and is minimally repaired at each failure between two successive PMs. Firstly, we determine the expected cost rate per unit time and the expected downtime per unit time for the periodic PM model. Then the overall value function suggested by Jiang and Ji(2002) is applied to obtain the optimal PM period and the optimal PM number. Finally, the numerical examples are presented for illustrative purpose.

• IE interfaces
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• v.19 no.3
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• pp.245-254
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• 2006

Equipments in container terminal have a lot of parts, and an equipment breakdown affects the productivity of terminal. In this paper, we develop a maintenance management system for improving reliability, availability and maintainability of equipments in container terminals. The developed system consists of five modules : equipment structure module, equipment operation management module, maintenance control module, spare part control module and data analysis module. The system supports reliability engineers to manage and improve RAM of equipments in container terminals. For example, FMEA, failure state analysis and life distribution parameters estimation are easily or automatically done by the system. This system also provides optimal preventive maintenance intervals by simulation and optimal yearly PM schedules for equipments in container terminal are recommended.

• Communications for Statistical Applications and Methods
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• v.9 no.3
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• pp.865-870
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• 2002

Burn-in is a widely used method to eliminate the initial failures. Preventive maintenance policy such as age replacement is often used in field operation. In this paper burn-in and maintenance policy are taken into consideration at the same time. The properties of the corresponding optimal burn-in times and optimal maintenance policy are discussed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.1
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• pp.274-283
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• 2016

The study of maintenance planning is important in military weapon systems because it can improve their availability and reduce the operational and maintenance cost during the total life cycle. In maintenance planning, it is important to determine the preventive maintenance task and its optimal interval. This paper focuses on the hard time task, which is one of the preventive maintenance tasks. A hard time task removes an item or restorative action before some specified maximum age limit to prevent functional failure. The Monte-Carlo simulation model was proposed to help understand the cost effectiveness of a hard time task. In the simulation, various shape parameters of the Weibull distribution and cost ratio of corrective maintenance to preventive maintenance were assumed. Using a Monte-Carlo simulation, a quantified cost saving effect and optimal preventive maintenance interval were suggested.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1997.10a
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• pp.193-196
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• 1997

In this paper we consider a Bayesian theoretic approach to periodic incomplete preventive maintenance with minimal repair at failure. We assume that the system failure rate is increasing as the frequency of PM increases and that the system is replaced at the K-th PM under this maintenance strategy. The optimal policies which minimize the expected cost rates are discussed. We seek the optimal periodic PM interval x and replacement time K under a Weibull failure intensity. Assuming suitable prior distribution for the Weibull parameters, we derive the posterior distribution incorporating failure data and obtain the updated optimal replacement strategies.

• Journal of Korean Society of Steel Construction
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• v.14 no.5 s.60
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• pp.627-639
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• 2002

Bridge construction is almost complete in many countries. Thus, the government and highway agencies change their focus from constructing to maintaining. Effectively maintaining bridges require predicting their lifespan using a system reliability viewpoint. Likewise, maintenance models based on the system reliability concept should be developed. Thus, this study developed maintenance models for preventive maintenance and essential maintenance using system reliability and lifetime distributions. The optimal maintenance strategy for an existing bridge was obtained using the developed maintenance models.

• Journal of Korean Institute of Industrial Engineers
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• v.37 no.4
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• pp.390-399
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• 2011

Generally the life-cycle cost of complex systems composed of several sub systems or equipments such as train, aircraft weapon systems is spent much more during operation and maintenance phase than development phase. The maintenance cost for maintaining the availability and extending the life span of systems comprise a large proportion of systems operation cost. The cycle of preventive maintenance affects operation and maintenance cost a lot. In this study we introduce a way minimizing life-cycle cost of systems by calculating more reliable preventive maintenance period than the results of previous study using systems reliability data considered the reliability and failure effect ratio of sub-systems or components. We can solve the preventive maintenance period problem known as NP-Hard as quick as possible by using modified genetic algorithm than using other models introduced in previous study.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.25 no.5
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• pp.276-284
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• 2013

A stochastic expected cost model has been suggested by combining the nonlinear cumulative damage model with the expected cost model together which can be useful for doing the preventive optimal-maintenance of the armor units of rubble-mound breakwaters. The suggested model has been satisfactorily calibrated by comparison of the results from others models, also the sensitivity analysis has been carried out in detail under the variation of the associated parameters with the model. The optimal repair times can be directly evaluated by minimizing the expected cost rates that depend on the social importances, damage intensity functions and resistance limits. Finally, the present cost model has been straightforwardly applied to the armor units of rubble-mound breakwaters. Based on the assumption of turning the damaged structure back to the state as good as new after repairs, the required optimal repair times and magnitudes can be determined quantitatively in terms of the optimum balance between the costs and benefits on the preventive maintenance.