• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.27 no.3
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• pp.7-15
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• 2013

In lighting design, the calculation of maintenance factor is performed by calculation considering light source, characteristics of luminaire and environmental factors. The method to calculate the current maintenance factor applied to tunnel lighting design takes into consideration only pollution factors in tunnels. In addition, the calculation method should be change in response to changes of tunnel conditions and used light sources. In this study, the calculated factor of the maintenance factor in tunnel is determine by four calculation factors generally applied to the calculation of maintenance factor. This study examined the method of calculating the maintenance factor of tunnel lighting that can be applied according to the installation conditions in designing tunnel lighting by applying the actual installation data of luminaire.

• Proceedings of the KIEE Conference
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• 2000.07c
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• pp.2153-2155
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• 2000

The not an organization a branch stream the maintenance factor class on a class and the roadway type for roadway lighting design, the facted an insufficiency maintenance factor to apply our the country conditions. The consideration of maintenance factors is not being fully applied for roadway lighting design in Korea. This paper consider optical characteristics and maintenance factors as well as LID of Luminaires in designing roadway lighting. Consideration of maintenance factors that are neme specified according to LDD(Luminaire Dirt Depreciation), LLD(Lamp Lumen Depreciation), AADT(Average Annual Daily Traffic) based on IESNA regulation. The analyzed optical characteristics are applied for stagger and cross roadway types with maintenance factors in the range of 0.51$\sim$1.00 and equipment factor of 0.9.

• Journal of Korean Institute of Industrial Engineers
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• v.36 no.2
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• pp.108-116
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• 2010

The maintenance of a deteriorating system is often imperfect. Previous studies have shown that the imperfect preventive maintenance (PM) can reduce the wear out and aging effects of deteriorating systems to a certain level between the conditions of as good as new and as bad as old. In this paper, we employ the concept of the improvement factor in investigating two optimal PM policies; failure limit policy and periodic PM policy. We redefine the improvement factor model as a function of the cost of PM, using this concept, we derive the conditions of optimal PM policies and formulate expressions to compute the expected cost rate. Based on this information, the determination of the maintenance policies which minimize the cost rate is examined. Numerical examples for the Weibull distribution case are also given.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2013.11a
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• pp.120-121
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• 2013

Apartment houses maintenance like remodeling in at issue and the importance is getting higher. On this study, we analyzed a variety of the influence factor affected building's maintenance expenses. circumstance influence factor about maintenance expenses is classified into region(big city, small and medium city), (area of high snowfall), (downpour region), (earthquake region), location(waterfront, inland province), using condition(mixed use, single use), frequency of use(kindergarten, middle school, high school), architecture method(reconstruction, construction).

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.12 no.2
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• pp.1-6
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• 1998

It is required to determine proper values for the maintenance factor according to traffic volume in the freeway lighting design. This paper presents a simple method to seperate of the effect of surrounding environment and that of traffic volume, which is based on the IESNA treatment with additional assumptions on their effects. Furthermore, it is found that prevailing concept for the maintenance factor does not necessarily yield a proper value for light loss factor, so that an additional factor of 0.9 should be included as an equipment factor.factor.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.41
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• pp.167-175
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• 1997

This study is concerned with Quality Maintenance System in Total Productive Maintenance. The important factor in manufacturing process is to attain the uniformity of quality Also quality assurance system is defined such as manufacturing process and products. In this paper, the design of quality maintenance system is considered to manufacturing process elements. Especially the manufacturing process is oriented to machinery equipments, repair and maintenance system is wide principal factor. And quality in manufacturing field is influenced by equipment maintenance system. So in the article, maintenance system for quality is given in a view of quality assurance. And the analysis of Physical Mechanism is explored in real field example.

• Journal of the Korean housing association
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• v.22 no.6
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• pp.51-60
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• 2011

The maintenance cost depends on various factors such as building volume, floor area, number of household and so on. The maintenance cost of the apartment housing is affected by the maintenance type, building physical factor, sociogeographic aspects. Among these, the maintenance characteristics is represented and made up by the total floor area and number of household which means main factor to provide the building scale roughly. In this paper, it aimed at modelling the estimation function of the maintenance cost with the total floor area and number of household and analyzing the elasticity of the two factors. Although items of maintenance cost are various in general cost, repair cost and so on, we classified these items into the 5 categories. 5 categories are a general cost, a facility maintenance cost, a utilization cost, insurance and sanitary cost. The estimation function used a power function and it has better goodness-offitness than any other estimation methods in statistics. A power function has a three curve types with concave and convex and linear style to the origin.

• Journal of Applied Reliability
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• v.11 no.2
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• pp.141-149
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• 2011

Environment Conversion Factors, which are stipulated in System Reliability Toolkit, have a lot of advantages once applied in a reliability data handbook such as NPRD-95, during the process of reliability prediction. However, the factors have a restriction in their applications because they don't deal with a few environments, e.g., Missile Launch (ML). In this study, environment factors of various components from MIL-HDBK-217F were analyzed to address this problem. Statistical computations showed that converting from Airborne Rotary Wing (ARW) to Missile Launch (ML) was the most coherent by comparing coefficient of determination. In addition, conversion factors from System Reliability Toolkit and those from the statistical calculations were evaluated in terms of their similarities.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.15 no.5
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• pp.1-7
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• 2001

Factors which affect largely the economics of lighting system, are initial installation costs, maintenance costs, energy costs as so on. In these costs, maintenance cost, lamp replacement labor cost, luminaire cleaning cost et al. so the economics of lighting system are evaluated different by maintenance planning. It is important to evaluate which lighting system would be economically advantageous in a initial design. In this study, the importance of maintenance factor is verified by the evaluations of the economics of lighting systems while maintenance factor is varied composition factors in ZCM which is used to calculate the average illuminance.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2019.05a
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• pp.246-247
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• 2019

This study was conducted to provide useful information to enable planned repair and cost planning during the operation and maintenance phase of aged multi-family housing. For this purpose, The concept of probabilistic maintenance cost analysis considering the risk factors of the aged multi-family housing is presented in the following six steps. 1. Risk factor investigation and analysis 2. Classification and deriving of maintenance cost 3. Investigation and deriving cost maintenance cost of old apartment house 4. Analysis of expert questionnaire 5. Analysis of Monte -Carlo simulation 6. Probabilistic maintenance cost Deriving the result. This study has limitations that need to be verified by applying actual data.