Earticle

This study is a theoretical analysis about the effectiveness of maintenance cost reduction which can be attained by deploying maintenance analysis according to CBM(Condition Based Maintenance) as it is gradually proved to be efficient in TBM(Time Based Maintenance). The benefits of applying CBM are manifold, e.g., Maintenance Cost Reduction, ability to analyze the cause of failure, enhanced availability of equipment, reduction in planned maintenance, reduced personnel for maintenance checking and reduction in additional cost caused by Breakdown. In this study, we focus on the analysis of Maintenance Cost since it takes the major part in cost reduction activity. Current maintenance practices of the Korean weapon system have been analyzed. And a case study has been performed to analyze the impact of maintenance cost reduction when CBM was deployed and customized to fit the Korean weapon system environment. This paper also analyzes the connected effect of CBM with Performance Based Logistics (PBL) and also with Contractor Logistics Support (CLS) which is planned to be adopted by the Korean Military Force.

Equipment and machine of industrial plant are give effect to mechanical-stress of many working-stop or long time operating. Therefore, to be old and decrepit of every king of equipment. As long time operating equipment period into increase conservation and of repair equipment time is efficacious necessity of utility factor gradually that of productivity of diminution and complete equipment expense of increase. Conservation at special skill working and necessity is that will effectually and complete a period prevention management diagnosis can conservation point at issues at in advance.

In this paper, we study structural changes and performance gains in condition-based maintenance process redesign when mobile IoT technology is embedded into urban railway rolling stock. We first develop condition-based maintenance To-Be process model in accordance with the IoT deployment scheme. Secondly, we draw upon theoretical framework of redesign process analysis to develop performance evaluation method suitable to predictive maintenance shift from As-Is ordinary maintenance practice. Subsequently, To-Be process performance evaluations are conducted adopting both the quantitative and qualitative method for time, cost, and dependability dimensions. The results ascertain the considerable benefits captured through detection abnormality prior to actual rolling stock failure occurrence, and details of performance improvements and enhancement of standardization level is revealed. The procedures and results presented in this paper offers useful insights in the fields of IoT economic analysis, condition based maintenance, and business process redesign.

최근 들어 센서 및 통신기술의 발달로 국내외 연구자들은 장비나 시스템의 상태정보를 수 집하여 진단 및 예측 기법을 통한 유지보수를 결정하는 방법론에 대해 연구를 활발히 진행하 고 있다. 본 연구에서는 이러한 연구 문헌 고찰을 통해 현시점의 차량부품 상태를 바탕으로 미래 시점까지의 차량부품 상태변화 추이를 예측하여 유지보수 의사결정을 수행하는 시스템 프레임워크를 제시하였다. 또한, 유지보수 활동에 따른 전과 후의 차량부품 상태변화 추적을 통해서 상태 진단 및 예측 데이터 조정이 가능하도록 구성하였다. 향후 본 연구 결과의 적용을 통해 대중버스를 이용하는 시민들의 안전과 차량의 상태기반 유지보수 체계 활성화에 조금이 나마 기여할 수 있기를 기대한다.

Recently, with the development of sensor and communication technology, researchers at home and abroad have actively conducted research on methodologies for determining maintenance through diagnosis and prediction techniques by collecting information on the status of equipment or systems. Based on the status of vehicle parts at this point in time, this study presented a system framework for making maintenance decisions by predicting the change in vehicle part status to a future date based on the current state of vehicle parts. In addition, condition diagnosis and predictive data adjustment was configured through tracking the status of vehicle parts before and after maintenance activities. We hope that the application of the results of this study will contribute a little to the safety of citizens using public buses and to the activation of the condition-based maintenance system of vehicles.

The non-homogeneous Poisson process (NHPP) has been a predominant model for describing the failure patterns on repairable systems. The condition monitoring method utilizes contemporary degradation models that combine component-specific, real-time failure data acquired during operation. This arises with the degradation and reliability characteristics of the component’s population to predict and update the residual life distribution (RLD). This study now proposes the decision-making process of depot maintenance cycle using NHPP and condition monitoring method to find the optimum depot maintenance cycle.

The repair of catapult is a complicated engineering. In this paper, the method of Condition Based Maintenance is applied into the repair system based on the catapult maintenance of system analysis. In view of the application of Condition Based Maintenance in the modern aviation equipment, the catapult availability is the final goal. The structure of catapult maintenance system is analyzed. The structure model of system dynamic feedback is established by using system dynamics method. Simulation is based on the "Nimitz" actual data of the Surge operation in 1997. The results prove the effectiveness and rationality of the proposed method. Through the analysis of the simulation evaluation results, the method applying Condition Based Maintenance into catapult repair system can improve catapult availability.

Fault prediction is the precondition of Condition Based Maintenance (CBM), accurate prediction for equipment can not only make warning before failure occurs, but also reduce the cost of maintenance of complicated equipment and system. Therefore, it is of profound importance to make research on fault prediction of electronic equipment. This paper analyses some typical fault prediction method of electronic equipment, and presented improvement measures for the practical problems, finally proposed a combination of fault prediction model, and it was applied to the electronic equipment with complex structure verification.

This paper considers a condition-based maintenance (i.e. CBM) model for the hydro generating unit in the deregulated power system. As the downtime cost of the generating unit varies according to the time-varying electricity price, the economic dependence among the critical component of the generating unit is dynamic. In this paper, the proposed Dynamic-Economic-Dependence and proportional hazards model based CBM policy considers the dynamic economic dependence among components as well as the reliability and the monitoring information of different critical components. An example for the hydro generating unit is presented to verify the effectiveness of the proposed condition based maintenance policy.

This paper considers a condition-based maintenance (i.e. CBM) model for the hydro generating unit in the deregulated power system. As the generating loss varies according to the time-varying inflows, the economic dependence among the critical component of the generating unit is dynamic. To reduce the maintenance cost effectively, we propose an inflow-dependent control-limit policy instead of the constant control-limit policy for CBM optimization. An example for the hydro generating unit is presented to verify the effectiveness of the proposed policy.

It is well known that condition based preventive maintenance (CBM) plays a key role in improving reliability of the devices and increasing security of the production process. But compared with traditional time based preventive maintenance (TBM), due to being an unplanned examining-maintenance activity beforehand, stationary operation of the devices is possibly interrupted so as to make whole production process become unstable, for example, connected-grid wind power generators, large-size nuclear power facilities, and railway transportation signals, and etc. Hence, in this paper the full life cycle model of the devices operation is firstly constructed with preventive maintenance (PM) involved, and then its reliability indexes and steady-state operation characteristics are analyzed with the model parameters being time-invariant corresponding to TBM. On the basis of it, the operation behavior of time-variant system is researched corresponding to CBM under some limitations, such as stability, accessibility, and controllability, and etc. The investigations indicate that TBM is a predictable and controllable process such that it can satisfy one’s expectation by selecting suitable model parameters, whereas CBM is usually unpredictable such that it can not arrive at desired aim. Therefore, based on the relationships of the two, this paper proposes a CBM control scheme based on TBM, and investigates the dynamical behavior and real-time characteristics of control systems. The goal to do this makes the CBM exhibit some expected behaviors like the TBM such that the behaviors of the time-variant system can meet the desired requirements. The investigation results show that the proposed technology is quite effective, and is fit to control stationary operating of the systems under CBM scene. And so the proposed method possesses certain theory instruction significances for PM maintenance practices for those large-scale production processes.

To improve operation maintenance management levels and increase economic profits for repairable devices, condition based preventive maintenance (CBM) has been widely applied in industrial enterprises in recent years. Compared with traditional time based maintenance (TBM), CBM not only can ensure the production process more safety but also dramatically reduce the examining-maintenance cost, which can be thought as a proactive maintenance scheme, practically. In this paper, we firstly construct the full life cycle model with four-state of the devices, and then simplified it into three-state model based on some practical considerations. On the basis of it, the paper analyzes its reliability operation characteristics under diverse maintenance models such as the proactive maintenance based on CBM, and the proactive maintenance based on TBM, and the passive maintenance, and the redundant maintenance scheme, and computes its desired maintenance cost and the investment payback period. The computing results show that the investments payback period is the shortest of the proactive maintenance rule based on CBM, and the one based on TBM comes second, and the one based on passive maintenance comes third, and the one of the redundant management model is the inferior. The investigations show that proactive maintenance based on CBM is a very effective operation maintenance management mode for repairable devices, and possesses very broad applications prosperity.

Industrial equipment reliability improvement and maintenance is gaining attention as the next great opportunity for manufacturing productivity improvement. Reactive maintenance is expensive because of extensive unplanned downtime and damage to machinery. To avoid such an unplanned machine downtime, it is needed to use proactive maintenance approach by either using historical maintenance data or by sensing machine conditions. This paper discusses failure diagonosis and prediction based on the condition-based maintenance and reliability technique. Thus, by enabling such a framework, it can bring us more efficient planning and execution of maintenance to reduce costs and/or increase profits.

The army’s runways are essential for the operation of army aviation weapon systems as they are maintained to ensure availability in needs. However, due to the lack of guidelines for partial runway maintenance, determining the appropriate time for maintenance is challenging, leading to inefficient budget use. This study aims to determine the minimum maintenance period after partial runway maintenance within realistic constraints using Markov chains. In order to decide the minimum maintenance period, crack rate, plastic deformation, and the number of days elapsed since the last maintenance are considered to define runway condition. In addition, we treat maintenance period as a variable. Transition probabilities and matrices are constructed based on the expected lifetime of each state change. By leveraging the characteristics of absorbing Markov chains, we estimated the daily expected cost of partial runway maintenance, the time until a complete resurfacing is needed, the average interval between partial maintenance, the total area requiring maintenance, and the proportion of time spent in a state requiring maintenance. By applying the minimum maintenance period after maintenance to our model, we compared performance measures defined above and finally identified the optimal minimum maintenance period.

This paper discusses condition based preventive replacement for deteriorating systems. The system continuouslydeteriorates in time and fails at any deterioration level which is always monitored, It is replaced at failure or atsome deteriorated level preventively before failure. The deterioration process is represented by a Weibulldistribution with a time-linear scale parameter. The cost rate function is formed considering replacement costand opportunity loss cost and deterioration dependent failure distribution, If the system has an increasingdeterioration dependent failure rate, the optimal deterioration level for preventive replacement can be determinedfrom minimizing the cost rate. An illustrative example is given for a Weibull deterioration dependent failuredistribution.

현재 많은 제조 업체들이 장비를 운영하는 중에 장비의 수명이나 이상으로 인한 고장으로 전체 작업 공정이 중단되어 큰 손실은 입은 많은 사례를 가지고 있다. 본 논문에서는 이러한 피해를 조금이나마 줄여 보고자 장비의 상태를 모니터링 및 분석하여 장비의 교체 시기 및 고장 의심 부분을 사용자에게 미리 알려주는 분석 툴을 설계한다. 실제 장비의 적용 대상은 현대중공업 LNG 선박 제조의 크레인 전동기를 대상으로 하였다. 특히, 크레인에서 가장 중요하다고 할 수 있는 전동기의 진동 데이터를 파형(Wavelet)화 하고, 이것을 FFT(Fast Fourier Transform) 변환하여 이 두 형태를 분석해서 전동기의 이상 징후를 발견하는데 초점을 맞추었다. 향후 이러한 적용 사례를 활용하게 되면, 고가 장비의 갑작스러운 고장으로 인한 제조업체의 손실을 조금이라도 줄일 수 있을 것으로 본다.

Purpose: We provide a condition-based maintenance policy where a surrogate variable is used for monitoring system performance. We constructed a risk function by taking into account the risk and losses accompanied with erroneous decisions. Methods: Assuming a unique degradation process for the performance variable and its specific relationship with the surrogate variable, the maintenance policy is determined. A risk function is developed on the basis of producer's and consumer's risks accompanied with each decision. With a strategic safety factor considered, the optimal threshold value for the surrogate variable is determined based on the risk function. Results: The condition-based maintenance is analyzed from the point of risk. With an assumed safety consideration, the optimal threshold value of the surrogate variable is provided for taking a maintenance action. The optimal solution cannot be obtained in a closed form. An illustrative numerical example and solution is provided with a source code of R program. Conclusion: The study can be applied to situation where a sensor signal is issued if the system performance begins to degrade gradually and reaches eventually its functional failure. The study can be extended to the case where two or more performance variables are connected to a same surrogate variable. Also estimation of the distribution parameters and risk coefficients should be further studied.

Purpose: This study proposes a process for evaluating the preventive maintenance policy for a system with degradation characteristics and for calculating the appropriate preventive maintenance cycle using time- and condition-based maintenance. Methods: First, the collected data is divided into the maintenance history lifetime and degradation lifetime, and analysis datasets are extracted through preprocessing. Particle filter algorithm is used to estimate the degradation lifetime from analysis datasets and prior information is obtained using LSE. The suitability and cost of the existing preventive maintenance policy are each evaluated based on the degradation lifetime and by using a minimum repair block replacement model of time-based maintenance. Results: The process is applied to the degradation of the reverse osmosis (RO) membrane in a seawater reverse osmosis (SWRO) plant to evaluate the existing preventive maintenance policy. Conclusion: This method can be used for facilities or systems that undergo degradation, which can be evaluated in terms of cost and time. The method is expected to be used in decision-making for devising the optimal preventive maintenance policy.

경사제 피복재를 예방적으로 유지관리할 수 있는 조건기반 할인비용모형을 제안하였다. 하중발생 사상을 이산시간 확률과정으로 고려하는 추계학적 누적 피해모형과 보수보강 비용에 대한 경제성 모형을 결합하여 수학적으로 유도하였다. 특히 본 논문에서 유도된 조건기반 유지관리의 할인비용모형은 시간에 따른 비용의 가치 뿐만 아니라 누적피해의 비선형성도 고려할 수 있다. 본 연구의 결과는 기존 모형들의 결과와 비교하여 만족스럽게 검증되었다. 또한 구조물의 중요도와 이자율 변화에 대한 민감도 분석도 수행하여, 구조물의 중요도가 높아질수록 예방적 보수보강의 최적시기는 빨라지나 이자율은 커질수록 반대의 경향이 나타난다는 것을 알았다. 한편 본 연구에서 유도된 추계학적 기대비용모형을 이용하여 여러 조건에 대하여 임의의 경사제 피복재 단면을 해석하였다. 표본경로기법을 적용하여 임의의 태풍 내습에 따른 경사제 피복재의 기대 누적피해수준을 예측하여 피해강도함수의 계수들을 추정할 수 있었다. 특히 하중발생 과정을 HPP(Homogeneous Poisson Process) 뿐만 아니라 DSPP(Doubly Stochastic Poisson Process)로도 해석하여 기대 누적피해수준에 미치는 하중발생의 불확실성에 대한 영향을 분석하여 하중발생사상을 이산시간 확률과정으로 고려해도 된다는 것을 확인하였다. 조건기반 할인비용모형의 해석 결과에 의하면 경사제 피복재의 설계조건에 따라 기대 누적피해수준의 거동특성이 크게 달라지고 이에 따라 예방적 보수보강을 수행하는 최적시기도 변한다는 것을 알 수 있었다. 마지막으로 파괴한계, 구조물의 중요도 그리고 이자율을 변화시키면서 예방적 유지관리를 가장 경제적으로 수행할 수 있는 최적시점과 피해규모를 결정할 수 있었다.

A discounted cost model for preventive maintenance of armor units of rubble-mound breakwaters is mathematically derived by combining the deterioration model based on a discrete-time stochastic process of shock occurrence with the cost model of renewal process together. The discounted cost model of condition-based maintenance proposed in this paper can take into account the nonlinearity of cumulative damage process as well as the discounting effect of cost. By comparing the present results with the previous other results, the verification is carried out satisfactorily. In addition, it is known from the sensitivity analysis on variables related to the model that the more often preventive maintenance should be implemented, the more crucial the level of importance of system is. However, the tendency is shown in reverse as the interest rate is increased. Meanwhile, the present model has been applied to the armor units of rubble-mound breakwaters. The parameters of damage intensity function have been estimated through the time-dependent prediction of the expected cumulative damage level obtained from the sample path method. In particular, it is confirmed that the shock occurrences can be considered to be a discrete-time stochastic process by investigating the effects of uncertainty of the shock occurrences on the expected cumulative damage level with homogeneous Poisson process and doubly stochastic Poisson process that are the continuous-time stochastic processes. It can be also seen that the stochastic process of cumulative damage would depend directly on the design conditions, thus the preventive maintenance would be varied due to those. Finally, the optimal periods and scale for the preventive maintenance of armor units of rubble-mound breakwaters can be quantitatively determined with the failure limits, the levels of importance of structure, and the interest rates.