• Smart Structures and Systems
• /
• v.20 no.6
• /
• pp.697-708
• /
• 2017

Maintenance plays a critical role in the bridge industry, but actual practices show many limitations because of traditional, 2D-based information systems. It is necessary to develop a new generation of maintenance information management systems for more reliable decision making in bridge maintenance. Enhancing current work processes requires a BIM-based 3D digital model that can use information from the whole lifecycle of a project (design, construction, operation, and maintenance) through continuous exchanges and updates from each stakeholder. This study describes the development of a data scheme for maintenance of cable-stayed bridges. We implemented the proposed system for a cable-stayed bridge and discussed its effectiveness.

• Journal of the military operations research society of Korea
• /
• v.34 no.3
• /
• pp.41-51
• /
• 2008

Advanced high-tech weapons have enormous affect on combat strength in modern warfare. However, lack of maintenance can cause decrease in equipment operating rate as well as decrease in expectation on demonstrative effect of combat strength during wartime. Therefore it is essential for combat readiness that the optimum requirement of equipment maintenance cost are forecasted and included in the budget. In this paper, the trend of equipment maintenance cost about K-111 1/4t military vehicle is first analyzed by evaluating the performance data of field operation. Secondly, based on above analyzed results, the forecasting model of equipment maintenance cost is designed. Finally, by applying this forecasting model, suggestion and estimation method of equipment maintenance cost have presented for the foreseeable future.

• Smart Structures and Systems
• /
• v.26 no.4
• /
• pp.533-544
• /
• 2020

Effective bridge maintenance reduces bridge operation costs and extends its service life. The possibility of storing bridge life-cycle data in a 3D parametric model of the bridge through Bridge Information Modeling (BrIM) provides new opportunities to enhance current practices of bridge maintenance management. This study develops a Decision Support System (DSS), namely BrDSS, which employs BrIM and an efficient optimization model for bridge maintenance planning. The BrIM model in BrDSS extracts basic data of elements required for the optimization process and visualizes the inspection data and the optimization results to the user to help in decision makings. In the optimization module of the DSS, the specifically formulated Genetic Algorithm (GA) eliminates the chances of producing infeasible solutions for faster convergence. The practicality of the presented DSS was explored by utilizing the DSS in the maintenance planning of a bridge under operation in the southwest of Iran.

• Journal of the Korean Data and Information Science Society
• /
• v.22 no.4
• /
• pp.775-784
• /
• 2011

In this paper, we consider the periodic preventive maintenance model for repairable system following the expiration of non-renewing free replacement-repair warranty (NFRRW). Under this preventive maintenance model, we derive the expressions for the expected cycle length, the expected total cost and the expected cost rate per unit time. Also, we determine the optimal preventive maintenance period and the optimal preventive maintenance number by minimizing the expected cost rate per unit time. Finally, the optimal periodic preventive maintenance policy is given for Weibull distribution case.

• Communications for Statistical Applications and Methods
• /
• v.13 no.3
• /
• pp.651-656
• /
• 2006

Wu and Clements-Croome (2005) investigate the optimization problem of PM policies for situations where the quality of PM is a random variable with a certain probability distribution. However, they assume that the cost of preventive maintenance is constant, not depending on the quality of PM. Thus, this paper considers a periodic PM model when PM cost depends on the quality of PM activity. The optimal PM policy are presented for the extended PM model and the numerical examples are presented for illustrative purpose.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.38 no.4
• /
• pp.505-516
• /
• 2018

In order to establish an efficient bridge maintenance strategy, the future performance of a bridge must be estimated by considering the current performance, which allows more rational way of decision-making in the prediction model with higher accuracy. However, personnel-based existing maintenance may result in enormous maintenance costs since it is difficult for a bridge administrator to estimate the bridge performance exactly at a targeting management level, thereby disrupting a rational decision making for bridge maintenance. Therefore, in this work, we developed a representative performance prediction model for each bridge element considering uncertainty using domestic bridge inspection data, and proposed a bayesian updating method that can apply the developed model to actual maintenance bridge with higher accuracy. Also, the feasibility analysis based on calculation of maintenance cost for monitoring maintenance scenario case is performed to propose advantages of the Bayesian-updating-driven preventive maintenance in terms of the cost efficiency in contrast to the conventional periodic maintenance.

• Journal of the Korea Society for Simulation
• /
• v.30 no.1
• /
• pp.65-73
• /
• 2021

The maintenance of the guided missiles typically requires the efficient management of spare parts and maintenance time. This study analyzed the impact of the maintenance time on operational availability. This study classifies the maintenance team with consideration of the skill level of the Harpoon guided missile maintenance and the goal is to analyze the impact on the operational availability with the skill levels quantitatively. Based on the real maintenance data of Harpoon guided missiles, a simulation model is constructed and analyzed. The analysis of the simulation result shows the trade-off between the maintenance time and operational availability. It is expected that the simulation model can help the maintenance policies of guided missiles.

• IE interfaces
• /
• v.17 no.spc
• /
• pp.122-130
• /
• 2004

Since the cost of software maintenance occupies about 50~75% in a general successful organization, the software maintenance plays an important role in software life cycle. In particular, if the managed system needs to be operated in a long term or the system is very large and complex, then the maintenance is especially more important. Software maintenance is defined as software modification activities after customer delivery, such as improvement of performance or functionality, error correction, adaptation to environmental changes, etc. In this paper, software cost estimation models are proposed, that is based on productivity of manpower in maintenance projects. In order to do this, the activities of maintenance are classified into function change, non-function change, user support and application operation. The proposed models are constructed and verified based on the real size and cost information of projects in the real world. The approach in this paper is to discriminate the heterogeneous activities in maintenance projects, and then to calculate the respective cost of each discriminated activity. By using the proposed models, the total cost of maintenance project is summed from the costs of four activities. In addition the number of conflicts between owner and order receiver about the amount of cost will be reduced and the reasonable cost estimation system will be established.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.28 no.4
• /
• pp.37-47
• /
• 2024

This study proposes a track maintenance quantity estimation model that considers evolution of rail fatigue damage and ballast settlement based on actual maintenance data from the Gyeongbu high-speed railway, and revises the existing life cycle cost (LCC) model for railway track. Using this model, maintenance quantities and life cycle costs based on different track quality levels are evaluated and discussed. According to the results, it is confirmed that applying the track maintenance quantity estimation model that accounts for rail fatigue damage and ballast settlement allows us to reasonably estimate maintenance costs close to the actual data. The track quality coefficient significantly influences both rail and ballast maintenance quantities, with ballast maintenance having a greater impact than rail maintenance. Additionally, as train speed increases, both rail and ballast maintenance quantities rise. Moreover, a higher track quality coefficient leads to a steeper increase in maintenance quantities with increasing train speed. Consequently, LCC also exhibits a faster growth rate over time with higher track quality coefficients and faster train speeds, resulting from an increased proportion of maintenance costs.

• Journal of Applied Reliability
• /
• v.16 no.4
• /
• pp.280-286
• /
• 2016

Purpose: Recently, Jiang defines the tradeoff B life to minimize a sum of life lost by preventive maintenance (PM) and corrective maintenance (CM) contribution parts and sets up an optimal replacement age of age replacement policy as this tradeoff life. In this paper, Jiang's model only considering the known lifetime distribution is extended by assigning different weights to two parts of PM and CM in order to reflect the practical maintenance situations in application. Methods: The new age replacement model is formulated and the meaning of a weight factor is expressed with the implied cost of failure under asymptotic expected cost model and also discussed with one-cycle expected cost criterion. Results: The proposed model is applied to Weibull and lognormal lifetime distributions and optimum PM replacement ages are derived with corresponding implied cost of failure. Conclusion: The new age replacement policy to escape the estimation of cost of failure in classical asymptotic expected cost criterion based on the renewal process is provided.