• Journal of Korean Society for Quality Management
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• v.40 no.1
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• pp.88-91
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• 2012

Joint optimization of preventive age replacement and inventory policy is considered in this paper. There are three decision variables in the problem: (i) preventive replacement age of the operating unit, (ii) order quantity per order and (iii) reorder point for spare replenishment. Preventive replacement age and order quantity are jointly determined so as to minimize the expected cost rate, and then the reorder point for meeting a desired service level is found. A numerical example is included to explain the joint optimization model.

• Journal of Korean Institute of Industrial Engineers
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• v.34 no.1
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• pp.98-107
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• 2008

The purpose of this paper is to present an optimization scheme that aims at minimizing the expected cost per unittime. This study considers a linear connected-(r, s)-ouI-of-(m, n):f lattice system whose components are orderedlike the elements of a linear (m, n)-matrix. We assume that all components are in the state 1 (operating) or 0(failed) and identical and s-independent. The system fails whenever at least one connected (r, s)-submatrix offailed components occurs. To find the optimal threshold of maintenance intervention, we use a simulatedannealing(SA) algorithm for the cost optimization procedure. The expected cost per unit time is obtained byMonte Carlo simulation. We also has made sensitivity analysis to the different cost parameters. In this study,utility maintenance model is constructed so that minimize the expense under full equipment policy throughcomparison for the full equipment policy and preventive maintenance policy. The full equipment cycle and unitcost rate are acquired by simulated annealing algorithm. The SA algorithm is appeared to converge fast inmulti-component system that is suitable to optimization decision problem.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.35 no.12
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• pp.181-188
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• 2019

The maintenance of school building is pivotal issue. However, it is difficult to obtain basic analysis data for LCC(Lifecycle Cost) analysis and maintenance planning of school building. Therefore, this study proposed System Dynamics(SD) techniques to make maintenance decisions for school building. The interaction between the major parameters related to the aging of a building, maintenance activities, and cost were expressed in Causal Loop Diagram. Based on this, the formula for the relationship between causal maps was defined and converted to Stock and Flow Diagram. Through the completed SD model the 50-year plan of 214 educational building were tested by considered in account budget, maintainability, and budget allocation opinions. As a result, the integrated SD model demonstrated that it can support strategic decision making by identifying the status class and LCC behavior of school buildings by scenario. According to the scenario analysis, the rehabilitation action of preventive maintenance that primarily repairs the buildings in condition grade C showed the best performance improvement effect relative to the cost. Therefore, if the proposed SD model is expanded to consider the effects of other educational policies, the crucial performance improvement budget can be estimated in the long-term perspective.

• Journal of Korean Society for Quality Management
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• v.28 no.3
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• pp.11-17
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• 2000

This paper presents a model for determining the optimal number of general repairs and supplementary input cost limit rate in addition to minimal repair cost rate to implement preventive maintenance. The basic concept parallels the periodic replacement model with minimal repair at failure introduced by Barlow and Hunter(1960) and Park(1979), only difference being the replacement signalled by the number of previous general repairs performed on the system. A general repair brings the state of the system to a certain better state than before repaired. Numerical examples are provided.

• Communications for Statistical Applications and Methods
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• v.12 no.1
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• pp.1-9
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• 2005

Burn-in is an engineering method which is used to eliminate early failures of products or systems after they have been produced. Recently, various models for determining optimal burn-in times have been developed, where some preventive maintenance policies were considered together with burn-in problem. In this paper, a survey of recent research in burn-in is undertaken.

• IE interfaces
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• v.4 no.2
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• pp.35-42
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• 1991

Many authors derived MTTF/MTBF for an operating system by analyzing its actual life time data. However, it is difficult to derive MTTF/MTBF when few breakdowns accur throughout a year. In this paper, we address a new approach to solve that problem under a preventive maintenance policy, in which few breakdowns occur, and also introduce a case study using the results obtained.

• Journal of Preventive Medicine and Public Health
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• v.54 no.4
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• pp.230-237
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• 2021

Objectives: This study explored changes in individuals' behavior in response to social distancing (SD) levels and the "no gatherings of more than 5 people" (NGM5) rule in Korea during the coronavirus disease 2019 (COVID-19) pandemic. Methods: Using survey data from the COVID-19 Behavior Tracker, exploratory factor analysis extracted 3 preventive factors: maintenance of personal hygiene, avoiding going out, and avoiding meeting people. Each factor was used as a dependent variable. The chisquare test was used to compare differences in distributions between categorical variables, while binary logistic regression was performed to identify factors associated with high compliance with measures to prevent transmission. Results: In men, all 3 factors were significantly associated with lower compliance. Younger age groups were associated with lower compliance with maintenance of personal hygiene and avoiding meeting people. Employment status was significantly associated with avoiding going out and avoiding meeting people. Residence in the capital area was significantly associated with higher compliance with personal hygiene and avoiding venturing out. Increasing SD levels were associated with personal hygiene, avoiding going out, and avoiding meeting people. The NGM5 policy was not significantly associated with compliance. Conclusions: SD levels, gender, age, employment status, and region had explanatory power for compliance with non-pharmaceutical interventions (NPIs). Strengthening social campaigns to inspire voluntary compliance with NPIs, especially focused on men, younger people, full-time workers, and residents of the capital area is recommended. Simultaneously, efforts need to be made to segment SD measures into substrategies with detailed guidance at each level.

• International Journal of Reliability and Applications
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• v.3 no.3
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• pp.113-124
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• 2002

This paper suggests the optimal periodic preventive maintenance policies after the combination warranty is expired. After the combination warranty is expired, a repairable system undergoes PM periodically and is minimally repaired at each failure. And also the system is replaced by a new system at the N th PM. In this case, we derive the mathematical formula for the expected cost rate per unit time. The optimal number and period for the periodic PM that minimize the expected cost rate per unit time are obtained. Some numerical examples are presented for illustrate purpose.

• Journal of the Korean Data and Information Science Society
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• v.20 no.6
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• pp.999-1007
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• 2009

This paper considers the optimal periodic preventive maintenance (PM) policy following the expiration of free-repair warranty. We assume that two periodic PM models with random maintenance quality which were proposed by Wu and Clements-Croome (2005) and Jung (2006b), respectively. Given the cost structure to the user during the cycle of the product, we derive the expressions for the expected cost rate per unit time. Also, we obtain the optimal PM number and the optimal PM period by minimizing the expected cost rate per unit time. The numerical examples are presented for illustrative purpose.

• Journal of the Korean Society of Safety
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• v.30 no.3
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• pp.13-19
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• 2015

Railway vehicle equipment goes back again to the state just before when failure by the repair. In repairable system, we are interested in the failure interval. As such, a statistical model of the point process, NHPP power law is often used for the reliability analysis of a repairable system. In order to derive a quantitative reliability value of repairable system, we analyze the failure data of the air brake system of the train line 7. The quantitative value is the failure intensity function that was modified, converted into a cost-rate function. Finally we studied the optimal number and optimal interval in which the costs to a minimum consumption point as cost-rate function. The minimum cost point was 194,613 (won/day) during the total life cycle of the braking system, then the optimal interval were 2,251days and the number of optimal preventive maintenance were 7 times. Additionally, we were compared to the cost of a currently fixed interval(4Y) and the optimum interval then the optimal interval is 3,853(won/day) consuming smaller. In addition, judging from the total life, "fixed interval" is smaller than 1,157 days as "optimal interval".