• Journal of Korean Institute of Industrial Engineers
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• v.31 no.4
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• pp.341-348
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• 2005

This paper is concerned with the question of servicing warranties for repairable items. During the warranty period, each time an item fails the manufacturer has the obligation to restore the item to operational condition either by repairing the item or by replacing it with a new item. In this paper, we consider repair-replacement strategies based on the condition of the failed item. For products with phase-type lifetime distributions where the phases represent the condition of the item, we develop algorithms to determine the expected cost of servicing a warranty and use it in making the repair-replacement decision. Illustrative numerical examples are presented. We also propose a dynamic strategy by taking the expected remaining warranty cost into consideration.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.686-691
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• 2005

We are concerned with the question of servicing warranties for repairable items. During the warranty period, each time an item fails the manufacturer has the obligation to restore the item to operational condition either by repairing the item or by replacing it by a new item. In this paper, we consider the repair-replacement strategies based on the condition of the failed item. For products with phase-type lifetime distributions where the phases represent the condition of the item, we develop algorithms to determine the expected cost of servicing a warranty and use it in making the repair-replacement decision. Illustrative numerical examples are presented. We also propose a dynamic strategy by taking the expected remaining warranty cost into consideration.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.3
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• pp.18-30
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• 2022

Predicting remaining useful life (RUL) becomes significant to implement prognostics and health management of industrial systems. The relevant studies have contributed to creating RUL prediction models and validating their acceptable performance; however, they are confined to drive reasonable preventive maintenance strategies derived from and connected with such predictive models. This paper proposes a data-driven preventive maintenance method that predicts RUL of industrial systems and determines the optimal replacement time intervals to lead to cost minimization in preventive maintenance. The proposed method comprises: (1) generating RUL prediction models through learning historical process data by using machine learning techniques including random forest and extreme gradient boosting, and (2) applying the system failure time derived from the RUL prediction models to the Weibull distribution-based minimum-repair block replacement model for finding the cost-optimal block replacement time. The paper includes a case study to demonstrate the feasibility of the proposed method using an open dataset, wherein sensor data are generated and recorded from turbofan engine systems.

• International Journal of Reliability and Applications
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• v.14 no.1
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• pp.41-54
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• 2013

In this paper, cost analysis is conducted using inter-failure interval under renewable warranty subject to imperfect repair for multi-component system. One way to model the imperfect repair is to use the quasi-renewal process (Wang and Pham 1996). Two alternative quasi-renewal processes were suggested by Park and Pham (2010) using quasi-renewal process; first is an altered quasi-renewal process with random variable parameter and second is a mixed quasi-renewal process considering replacement service and repair service, simultaneously. In this study, we use the altered and mixed quasi-renewal processes and develop the warranty cost model to obtain the expected value of warranty cost and to help company make important decisions regarding the warranty policy. Numerical examples are used to demonstrate the applicability of the methodology derived in the paper.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1997.10a
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• pp.193-196
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• 1997

In this paper we consider a Bayesian theoretic approach to periodic incomplete preventive maintenance with minimal repair at failure. We assume that the system failure rate is increasing as the frequency of PM increases and that the system is replaced at the K-th PM under this maintenance strategy. The optimal policies which minimize the expected cost rates are discussed. We seek the optimal periodic PM interval x and replacement time K under a Weibull failure intensity. Assuming suitable prior distribution for the Weibull parameters, we derive the posterior distribution incorporating failure data and obtain the updated optimal replacement strategies.

• Clinical and Experimental Pediatrics
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• v.48 no.8
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• pp.806-812
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• 2005

Repair mechanisms in the postnatal and mature central nervous system(CNS) have long been thought to be very limited. However recent works have shown that the mature CSN contains neural progenitors, precursors, and stem cells that are capable of generating new neurons, astrocytes, and oligodendrocytes especially in germinative areas such as the subventricular zone of the lateral ventricles, the dentate gyrus of the hippocampus. These findings raise the possibilities for the development of novel neural repair strategies via mobilization and replacement for dying neurons of neural stem cells in situ. Indeed recent reports have provided evidences that endogenous stem cells are activated in response to various injuries, and in some injury models, limited neuronal replacement occurs in the CNS. Here, current understandings for endogenous neurogenesis and induction neurogeneis in postnatal CNS including neonatal brain are summarized and discussed.

• Computational Structural Engineering : An International Journal
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• v.1 no.1
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• pp.71-80
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• 2001

A reliability approach to evaluate structural performance has gained increased acceptability and usage over the past two decades. Most reliability analyses are based on the reliability of an individual component without examining the entire structural system. These analyses often result in either unnecessary repairs or unsafe structures. This study uses examples of series, parallel, and series-parallel models of structural systems to illustrate how the component reliabilities affect the reliability of the entire system. The component-system reliability interaction can be used to develop optimum lifetime inspection and repair strategies for structural systems. These examples demonstrate that such strategies must be based on the reliability of the entire structural system. They also demonstrate that the location of an individual component in the system has a profound effect on the acceptable reliability of that component. Furthermore, when a structure is deteriorating over time, the reliability importance of various components is a1so changing with time. For this reason, the most critical component in the early life of the structure may not tie the most critical later.

• Computers and Concrete
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• v.8 no.5
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• pp.541-561
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• 2011

The Finite Element Method (FEM) was employed to demonstrate that accurate simulations of seismically repaired and retrofitted reinforced concrete shear walls can be achieved provided a good analysis program with comprehensive models for material and structural behaviour is used. Furthermore, the analysis tool should have the capability to retain residual damage experienced by the original structure and carry it forward in the repaired and retrofitted structure. The focus herein is to provide quick, simple, but reliable modelling procedures for repair and retrofitting strategies such as concrete replacement, addition of diagonal reinforcing bars, bolting of external steel plates, and bonding of external steel plates and fibre reinforced polymer sheets, thus illustrating versatility in the modelling. Slender, squat, and slender-squat shear walls were investigated. The modelling utilized simple rectangular membrane elements for the concrete, truss bar elements for the steel and FRP retrofitting materials, and bond-link elements for the bonding interface between steel or FRP to concrete. The analyses satisfactorily simulated seismic behaviour, including lateral load capacity, displacement capacity, energy dissipation, hysteretic response, and failure mode.

• 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.

• International conference on construction engineering and project management
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• 2007.03a
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• pp.837-847
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• 2007

The study focused on the evaluation of maintenance management strategies used in public hospital buildings in Lagos state. It also assessed the labour composition for maintenance operations. In achieving these objectives, opinions of maintenance officers of ten (10) different hospitals in different local government areas of the state were sampled through well structured questionnaires. The data collected were analyzed using descriptive and inferential statistics. From the analysis, the study revealed that majority of those public hospitals do not have specific budget for maintenance programmes, maintenance policies, maintenance log book and maintenance manual to guide the operatives. About 98% of them do not understand the type of maintenance strategy being used for their maintenance operations. 78% of the maintenance work are only executed when there is a breakdown or in response to user's request. For labour composition, the cleaning of interior and exterior of the building, inspection of building elements, repairs and replacements of building elements are mainly carried out by in-house staff, while the repair and replacement of equipment is by outsourcing. The study also revealed that using in- house staff, reduces costs and provides a higher security while outsourcing provides more flexibility in staffing reduces equipment expenditures and provide better access to special skills. The study recommended proactive measures to provide necessary training and support for maintenance staff and users of these facilities and a means of securing sufficient funds for maintenance programmes.