• International Journal of Reliability and Applications
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• v.18 no.1
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• pp.9-20
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• 2017

In this paper, we consider a renewable repair-replacement warranty strategy with age-dependent minimal repair service and propose an optimal maintenance model during post-warranty period. Such model implements the repair time limit under warranty and follows with a certain form of system maintenance strategy when the warranty expires. The expected cost rate is investigated per unit time during the life period of the system as for the standard for optimality. Based on the cost design defined for each failure of the system, the expected cost rate is derived during the life period of the system, considering that a renewable minimal repair-replacement warranty strategy with the repair time limit is provided to the customer under warranty. When the warranty is finished, the maintenance of the system is the customer's responsibility. The life period of the system is defined and the expected cost rate is developed from the viewpoint of the customer's perspective. We obtain the optimal maintenance strategy during the maintenance period by minimizing such a cost rate after a warranty expires. Numerical examples using field data are shown to exemplify the application of the methodologies proposed in this paper.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.96-104
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• 2017

A one-shot system (device) refers to a system that is stored for a long period of time and is then disposed of after a single mission because it is accompanied by a chemical reaction or physical destruction when it operates, such as shells, munitions in a defense weapon system and automobile airbags. Because these systems are primarily related with safety and life, it is required to maintain a high level of storage reliability. Storage reliability is the probability that the system will operate at a particular point in time after storage. Since the stored one-shot system can be confirmed only through inspection, periodic inspection and maintenance should be performed to maintain a high level of storage reliability. Since the one-shot system is characterized by a large loss in the event of a failure, it is necessary to determine an appropriate inspection period to maintain the storage reliability above the reliability goal. In this study, we propose an optimal inspection policy that minimizes the total cost while exceeding the reliability goal that the storage reliability is set in advance for the one-shot system in which periodic inspections are performed. We assume that the failure time is the Weibull distribution. And the cost model is presented considering the existing storage reliability model by Martinez and Kim et al. The cost components to be included in the cost model are the cost of inspection $c_1$, the cost of loss per unit time between failure and detection $c_2$, the cost of minimum repair of the detected breakdown of units $c_3$, and the overhaul cost $c_4$ of $R_s{\leq}R_g$. And in this paper, we will determine the optimal inspection policy to find the inspection period and number of tests that minimize the expected cost per unit time from the finite lifetime to the overhaul. Compare them through numerical examples.

• Journal of Korean Academy of Nursing
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• v.41 no.4
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• pp.500-509
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• 2011

Purpose: Time-driven activity-based costing was applied to analyze the nursing activity cost and efficiency of a medical unit. Methods: Data were collected at a medical unit of a general hospital. Nursing activities were measured using a nursing activities inventory and classified as 6 domains using Easley-Storfjell Instrument. Descriptive statistics were used to identify general characteristics of the unit, nursing activities and activity time, and stochastic frontier model was adopted to estimate true activity time. Results: The average efficiency of the medical unit using theoretical resource capacity was 77%, however the efficiency using practical resource capacity was 96%. According to these results, the portion of non-added value time was estimated 23% and 4% each. The sums of total nursing activity costs were estimated 109,860,977 won in traditional activity-based costing and 84,427,126 won in time-driven activity-based costing. The difference in the two cost calculating methods was 25,433,851 won. Conclusion: These results indicate that the time-driven activity-based costing provides useful and more realistic information about the efficiency of unit operation compared to traditional activity-based costing. So time-driven activity-based costing is recommended as a performance evaluation framework for nursing departments based on cost management.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.409-416
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• 2009

This paper presents a tool called Quality-Cost optimization system (QCOS), which integrates Multi-Objective Genetic Algorithm (MOGA) and Quality Function Deployment (QFD), for tradeoff between quality and cost of the unitized metal curtain-wall unit. A construction owner as the external customer pursues to maximize the quality of the curtain-wall unit. However, the contractor as the internal customer pursues to minimize the cost involved in designing, manufacturing and installing the curtain-wall unit. It is crucial for project manager to find the tradeoff point which satisfies the conflicting interests pursued by the both parties. The system would be beneficial to establish a quality plan satisfying the both parties. Survey questionnaires were administered to the construction owner who has an experience of curtain-wall project, the architects who are the independent assessor, and the contractors who were involved in curtain-wall design and installation. The Customer Requirements (CRs) and their importance weights, the relationship between CRs and Technical Attributes (TAs) consisting of a curtain-wall unit, and the cost ratios of each components consisting curtain-wall unit are obtained from the three groups mentioned previously. The data obtained from the surveys were used as the QFD input to compute the Owner Satisfaction (OS) and Contractor Satisfaction (CS). MOGA is applied to optimize resource allocation under limited budget when multi-objectives, OS and CS, are pursued at the same time. The deterministic multi-objective optimization method using MOGA and QFD is extended to stochastic model to better deal with the uncertainties of QFD input and the variability of QFD output. A case study demonstrates the system and verifies the system conformance.

• Communications for Statistical Applications and Methods
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• v.15 no.6
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• pp.909-923
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• 2008

This paper considers the replacement model and the preventive maintenance model following the expiration of combination warranty for a repairable system. If the system fails after the combination warranty is expired, then it is minimally repaired at each failure. The criterion used to determine the optimal replacement policy and the optimal preventive maintenance policy is the overall value function based on the expected cost rate per unit time and the expected downtime per unit time. The numerical examples are presented for illustrative purpose when the failure time follows a Weibull distribution.

• Journal of Information Technology Services
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• v.12 no.4
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• pp.255-265
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• 2013

This paper proposes a DEA-AR model for the efficiency evaluation of the iron ore brands in an integrated steel mill. The input factor is defined as unit cost of each brand based on CIF and two output factors are chosen as Fe and Al which are the important ingredients of iron ore. The relative importance between two output factors is determined by several experts using AHP model. The efficiency of each brand is determined using DEA and DEA-AR models. The negative correlation between the DEA-AR efficiency and the unit cost (CIF) is shown as significant whereas no significant correlation exist between the efficiency and the output factors. Also, the Kruskal Wallis rank sum test shows that there exist efficiency differences among the iron ore types whereas no difference is shown among the countries. The result could be utilized in selecting good brands of iron ores based on the DEA-AR efficiency in an integrated steel mill.

• Proceedings of the Korean Reliability Society Conference
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• 2005.06a
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• pp.121-129
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• 2005

In this paper, we consider a periodic preventive maintenance(PM) policy in which each PM reduces the hazard rate of amount proportional to the failure intensity, which increases since the last PM and slows down the wear-out speed to that of new one. And the proportion of reduction in hazard rate decreases with the number of PMs. Our model is similar to $ARI_1$ proposed by Doyen and Gaudoin(2004) in the sense of reduction of hazard rate. Our model has totally different wear-out pattern of hazard rate after PM's, however, and the proportion of reduction depends on the number of PM's. Assuming that the system undergoes only minimal repairs at failures between PM's, the expected cost rate per unit time is obtained. The optimal number N of PM and the optimal period x, which minimize the expected cost rate per unit time are discussed. Explicit solutions for the optimal periodic PM are given for the Weibull distribution case.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.285-288
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• 1996

This paper deals with an (s, S) spare-part inventory model with general leadtime. In the model, if the inventory level falls to a reorder point s, a replenishment order quantity Q is ordered. Assumming that the number of operating units is one and the lifetime of a unit follows an exponential distribution, we derive the expected cost rate and suggest a procedure to obtain the optimal pair of (s, S) minimizing the cost rate.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2012.11a
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• pp.283-284
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• 2012

High-rise building construction has been increasing for the recent years and the construction process has become more complicated. This suggests a need for precise planning based on reliable data to prevent cost overruns and delays. However, the process planning is implemented based mainly on the experience of engineers that can result in critical damage in cost and time. Accurate productivity estimation and unit cost analysis must be considered important matter to prevent such disaster. This study estimates productivity and unit cost of curtain wall operations in high-rise building construction by simulation techniques and statistical methodologies. This study suggests a decision making methodology for the site personnel that enables to compare various combinations of productivity and unit cost based on reliable data that has been collected in actual construction sites. It is expected that this study contributes to the following research of developing an optimized construction performance assembling model for the site personnel.

• Journal of Korean Institute of Industrial Engineers
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• v.24 no.1
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• pp.157-165
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• 1998

This paper considers the single-product production and transportation problem with discrete time, dynamic demand and finite time horizon, an extension of classical dynamic lot-sizing model. In the model, multiple freight container types are allowed as the transportation mode and each order (product) placed in a period is shipped immediately by containers in the period. Moreover, each container has type-dependent carrying capacity restriction and at most one container type is allowed in each shipping period. The unit freight cost for each container type depends on the size of its carrying capacity. The total freight cost is proportional to the number of each container type employed. Such a freight cost is considered as another set-up cost. Also, it is assumed in the model that production and inventory cost functions are dynamically concave and backlogging is not allowed. The objective of this study is to determine the optimal production policy and the optimal transportation policy simultaneously that minimizes the total system cost (including production cost, inventory holding cost, and freight cost) to satisfy dynamic demands over a finite time horizon. In the analysis, the optimal solution properties are characterized, based on which a dynamic programming algorithm is derived. The solution algorithm is then illustrated with a numerical example.