• Journal of the military operations research society of Korea
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• v.15 no.1
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• pp.54-62
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• 1989

This paper presents a corrective maintenance model to determine either type of maintenance actions upon failure of the system. Types of maintenance actions considered are minimal repair and replacement. Minimal repair cost is assumed to be random, whereas replacement cost is fixed. A policy, B(t), which determines the type of maintenance action based on the estimated minimal repair cost when the system fails at time t is adopted. To obtain an optimal policy, an expected maintenance cost per unit time is derived and is minimized with respect to B(t).

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.2
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• pp.24-31
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• 2018

As a system complexity increases and technology innovation progresses rapidly, leasing the equipment is considered as an important issue in many engineering areas. In practice, many engineering fields lease the equipment because it is an economical way to lease the equipment rather than to own the equipment. In addition, as the maintenance actions for the equipment are costly and need a specialist, the lessor is responsible for the maintenance actions in most leased contract. Hence, the lessor should establish the optimal maintenance strategy to minimize the maintenance cost. This paper proposes two periodic preventive maintenance policies for the leased equipment. The preventive maintenance action of policy 1 is performed with a periodic interval, in which their intervals are the same until the end of lease period. The other policy is to determine the periodic preventive maintenance interval minimizing total maintenance cost during the lease period. In addition, this paper presents two decision-making models to determine the preventive maintenance strategy for leased equipment based on the lessor's preference between the maintenance cost and the reliability at the end of lease period. The structural properties of the proposed decision-making model are investigated and algorithms to search the optimal maintenance policy that are satisfied by the lessor are provided. A numerical example is provided to illustrate the proposed model. The results show that a maintenance policy minimizing the maintenance cost is selected as a reasonable decision as the lease term becomes shorter. Moreover, the frequent preventive maintenance actions are performed when the minimal repair cost is higher than the preventive maintenance cost, resulting in higher maintenance cost.

• Computers and Concrete
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• v.17 no.4
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• pp.499-521
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• 2016

In this paper, a probabilistic- and finite element-based approach to evaluate and predict the lifetime performance of reinforced concrete (RC) bridges undergoing various maintenance actions is proposed with the time-variant system reliability being utilized as a performance indicator. Depending on their structural state during the degradation process, the classical maintenance actions for RC bridges are firstly categorized into four types: Preventive type I, Preventive type II, Strengthening and Replacement. Preventive type I is used to delay the onset of steel corrosion, Preventive type II can suppress the corrosion process of reinforcing steel, Strengthening is the application of various maintenance materials to improve the structural performance and Replacement is performed to restore the individual components or overall structure to their original conditions. The quantitative influence of these maintenance types on structural performance is investigated and the respective analysis modules are written and inputted into the computer program. Accordingly, the time-variant system reliability can be calculated by the use of Monte Carlo simulations and the updated the program. Finally, an existing RC continuous bridge located in Shanghai, China, is used as an illustrative example and the lifetime structural performance with and without each of the maintenance types are discussed. It is felt that the proposed approach can be applied to various RC bridges with different structural configurations, construction methods and environmental conditions.

• IE interfaces
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• v.16 no.1
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• pp.27-33
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• 2003

The maintenance cost in K Steelworks has been continuously increased in proportion to the production cost. However, there seems to be a possibility of reducing cost through the optimization of maintenance actions. The failure types of the equipment in steelworks ate various with different failure cost. Thus the failure rate and cost of each type of failures should be considered simultaneously when the optimum maintenance period is to be determined. It is considered that the equipment undergoes periodic replacement and a specified number of incomplete preventive maintenance actions are performed during a replacement period. Assuming that the time to failure follows a Weibull distribution, the parameters of the failure rate are estimated using the maximum likelihood estimation. The optimal replacement period is determined to minimize the average cost per unit time. As the result of analysis it is suggested that the existing maintenance period for a hot-rolling equipment can be extended significantly.

• Smart Structures and Systems
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• v.30 no.6
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• pp.571-582
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• 2022

Optimal life-cycle management is a challenging issue for deteriorating regional bridges. Due to the complexity of regional bridge structural conditions and a large number of inspection and maintenance actions, decision-makers generally choose traditional passive management strategies. They are less efficiency and cost-effectiveness. This paper suggests a deep reinforcement learning framework employing double-deep Q-networks (DDQNs) to improve the life-cycle management of deteriorating regional bridges to tackle these problems. It could produce optimal maintenance plans considering restrictions to maximize maintenance cost-effectiveness to the greatest extent possible. DDQNs method could handle the problem of the overestimation of Q-values in the Nature DQNs. This study also identifies regional bridge deterioration characteristics and the consequence of scheduled maintenance from years of inspection data. To validate the proposed method, a case study containing hundreds of bridges is used to develop optimal life-cycle management strategies. The optimization solutions recommend fewer replacement actions and prefer preventative repair actions when bridges are damaged or are expected to be damaged. By employing the optimal life-cycle regional maintenance strategies, the conditions of bridges can be controlled to a good level. Compared to the nature DQNs, DDQNs offer an optimized scheme containing fewer low-condition bridges and a more costeffective life-cycle management plan.

• Architectural research
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• v.7 no.2
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• pp.81-89
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• 2005

Over the years, existing bridges have had various degrees of maintenance to extend the service life. As the existing bridges continue to deteriorate, however, each Department of Transportation (DOT) of the United States of America faces increasing demands on the limited funds available for bridge maintenance. Therefore, it is very important for State Department of Transportations to establish Maintenance, Repair, and Rehabilitation (MR&R) strategies for bridge structures such that funds get allocated for appropriate maintenance over the service life. This paper identifies the state-of-art and the state-of-practice of MR&R actions and the use of MR&R strategies in concrete bridge decks. In addition, a questionnaire survey was conducted to identify the type and timing for MR&R actions as well as existing MR&R strategies taken in concrete bridge deck by each DOT. This paper also presents the results of the survey.

• Smart Structures and Systems
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• v.15 no.3
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• pp.609-625
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• 2015

Management of infrastructure stock is essential in sustainability of society, and its analysis and optimization are studied in the light of control system modeling in this paper. At the first part of the paper, cost of stock management is analyzed based on macroscopic statistics on infrastructure stock and economical growth. Stock management burden relative to economy is observed to become larger at low economic growth periods in developed economies. Then, control system modeling of stock management is introduced and by augmenting maintenance actions as control input, dynamic behavior of stock is simulated and compared with existing time history statistics. Assuming steady state conditions, applicability of the model to cross sectional data is also demonstrated. The proposed model is enhanced so that both preventive and corrective maintenance can be included as system inputs, i.e., feedforward and feedback control inputs. Optimal management strategy to achieve specified deteriorated stock level with minimal cost, expressed in terms of preventive and corrective maintenance actions, is derived based on estimated parameter values for corrosion of steel bridges. Relative cost effectiveness of preventive maintenance is shown when target deteriorated stock level is lower.

• Proceedings of the Korean Reliability Society Conference
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• 2004.04a
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• pp.29-37
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• 2004

Maintenance are actions (or activities) needed to (i) control equipment degradation and failures and (ii) to restore a failed equipment to operational state. The former is termed Preventive Maintenance (PM) and the latter as Corrective Maintenance (CM).(omitted)

• IE interfaces
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• v.15 no.3
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• pp.286-296
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• 2002

Products which are sold with warranty, preventive maintenance actions by manufacturers and/or buyers have an impact on the total costs for both parties. In this paper, we develop the models to study the expected warranty cost for products with free repairable warranty with three types of discrete preventive maintenance. We deal with by utilizing the concept that preventive maintenance reduces the virtual age of the system. We assume that the maintenance planning horizon can be segmented into k discrete and equally sized periods. In such a scenario, numerical examples are presented.

• Journal of the Korean Operations Research and Management Science Society
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• v.6 no.2
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• pp.7-11
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• 1981

An inspection-maintenance policy is investigated for a system having various states. A policy is characterized by the type of maintenance and the next inspection time. Maintenance actions are classified into various types according to the depth of maintenance. Policy evaluation criterion is the expected cost accumulated up to the failure of the system. The problem is formulated as a Markov decision process and an optimal policy is found by using a policy improvement procedure. A numerical example illustrates the policy for a system having five states.