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.

PURPOSES : The aim of this study is to determine the maintenance costs for a reasonable preliminary feasibility study, feasibility study, or evaluation METHODS : This study was based on government budget execution and budget execution data for expressways, national highways, cable-supported bridges and long-tunnels. For the expressway, data obtained from the Korea Expressway Corporation were used. For the national highway, data was obtained from the Ministry of Land, Infrastructure and Transport. Similarly, data collected from expressway maintenance costs and the Korea Infrastructure Safety and Technology Corporation were used for long tunnels and cable-supported bridges, respectively. The items for highway maintenance cost were reclassified more rationally to facilitate the calculation of the maintenance costs. The replacement cycle for each item was also calculated based on the budget expenditure data. RESULTS : The results of this study showed the standard maintenance cost model for expressways, national highways, cable-supported bridges, and long-tunnels. In other words, a basis for predicting reasonable maintenance costs was prepared for a feasibility study. CONCLUSIONS : The reliability of the maintenance cost results was improved and it was more consistent with actual costs compared to the results of previous studies. It can be used as a basis for estimating the maintenance cost of a preliminary feasibility study and feasibility evaluation in the future.

For the asset management of a water pipe network, it would be necessary to understand the extent of the maintenance cost required for the water pipe network for the future. This study would develop a method to draw the optimum cost required for the maintenance of the water pipe network in waterworks facilities to maintain the aim revenue water ratio and to achieve the target revenue water ratio, considering the water service providers’ waterworks condition and revenue water ratio comprehensively. This study conducted a survey with 96 water service providers as of the early 2015 and developed models to estimate the optimum maintenance cost of the water pipe network, considering the characteristics of the water service providers. Since the correlation coefficient of all the developed models was higher than 0.95, it turned out that it had significant reliability, which was statistically significant. As a result of applying the developed models to the actual water service providers, it was drawn that increasing revenue water ratio to more than a certain level can reduce the maintenance cost of the water pipe network by a great deal. In other words, it is judged that it would be the most efficient to secure the reliability of waterworks management by increasing the short-term revenue water ratio to more than a certain level and gradually increase the revenue water ratio from the long-term perspective. It is expected that the proposed methodology proposed in this study and the results of the study will be used as a basic research for planning the maintenance of water pipe network or establishing a plan for waterworks facilities asset management.

This study introduces the methods to apply and develop the integrated Cost of Quality (COQ) and Time-Driven Activity-Based Costing (TDABC) model for seeking not only quality improvement but also reduction of overhead cost. Inefficient and uneconomical COQ activities can be identified by using time driver which also maximizes the quality improvement for Prevention-Appraisal- Failure (PAF) quality costs. In contrast, reduction of the indirect cost of unused capacity resource using Quality Cost Capacity Ratio (QCCR) of TDABC minimizes overhead cost for COQ activities. In addition, linkage between Overall Equipment Effective (OEE) and Time Driver develops the integrated system of Total Productive Maintenance (TPM) and TDABC model. Lean OEE maximizes when an Unused Time (UT) of TDABC that are TPM losses and lean wastes reduces whereas the TPM Cost Capacity Ratio (TCCR) of TDABC minimizes indirect cost for non-value added TPM activities. Numerical examples are derived to better understand the proposed COQ/TDABC model and TPM/TDABC model from this paper. From the proposed model, process mapping and time driver of TDABC are known to lessen indirect cost from general ledger of comprehensive income statement with a better quality innovation and improvement of equipment.

실적공사비 적산방식은 품셈견적, 실측견적, 단가견적, 및 총액견적 등 매우 다양하다. 표준품셈은 공공기관 및 민간기관의 공사비 책정기준이 되는 자료이다. 본 논문에서는 도로공사에 이용되는 기존 품셈견적의 문제점을 개선하기 위해 현장조사를 실시하고 분석하였으며 그 결과로 각 공종에 대한 실측견적 방법을 통계적 방법을 통해 제시하였다. 또한, 기존 품셈과 실측품셈을 공사단위의 비교를 통해 제안된 품셈이 보다 간단한 견적 작성을 가능하게 하고 보다 현실적인 공사금액을 산출함을 알 수 있었다. 본 연구에서는 보조기층의 Case-Study를 통하여 각 방식별 장단점을 가시적으로 비교해 보았다. 실측품셈으로 적용하였을 경우, 계산과정은 기존품셈의 50%로 축소되었으며 1일 1장비 사용으로 기존의 1일미만 장비 사용에 대한 편차가 보완되었다. 또한 품셈만을 이용하여 공정의 시공내용을 짐작하고 이를 바탕으로 공정계획이나 인력투입계획 등을 수립할 수 있었다.

  Engineers are always concerned with life cycle costs for making important economic decisions through engineering action like reliability of products. Decisions during the reliability growth development of products involve trade-offs between invested cos

In this paper, we developed a predictive model of maintenance and repair cost based on the element-level condition state by using information collected through the inspection/diagnosis of individual bridges for use in maintenance strategy analysis. The reliability of the prediction model can be improved through of big data analysis using various factors and additional data.

The purpose of this study was to suggest the foundation of LDA-based model for infrastructure maintenance cost evaluation. The LDA-based model enables to evaluate not only overall maintenance cost, but also various combination of each cell of risk matrix.

The purpose of this study was to suggest the foundation of LDA-based model for infrastructure maintenance cost evaluation. The LDA-based model enables to evaluate not only overall maintenance cost, but also various combination of each cell of risk matrix.

본 논문은 교량의 예방적 유지관리 효과를 생애주기비용 절감 측면에서 분석 하였다. 예방적 유지관리는 현재 실시되고 있는 대응 적 유지관리 전략과 대비 되는 유지관리 전략으로 교량의 열화지연을 통해 궁극적으로는 교량의 사용수명을 연장 시키며 생애주기비용을 절 감시키는 유지관리 전략이다. 이러한 예방적 유지관리 효과를 분석하기 위해 교량의 공용연수에 따른 건전도 점수 변화 모델과 FHWA 자료를 바탕으로 한 국내 고속도로 교량의 건전도 점수에 따른 보수·보강 비용 모델을 제시 하였다. 제시한 복수의 모델과 국내외 참고 문헌을 바탕으 로 제안된 예방적 유지관리 항목(청소와 도장)의 비용과 주기를 활용하여 사용수명 100년까지의 표준교량(1,730 m2/교량) 당 생애주기 비용과 향후 20년간의 고속도로 총 유지관리 비용을 산정 하였다. 분석 결과 100년간 예방적 유지관리 활동으로 인해 교량 당 5억원의 절감효과를 볼 수 있으며 현재 예방적 유지관리 활동을 실시할 경우 20년 후(2035년)에는 총 1,837억원, 즉 연간 약 92억원의 비용 절감효과를 볼 수 있는 것으 로 분석 되었다.

The Goal of research is that budget of maintenance were estimated in network-level bridges. We determined the life cycle of exchangeable bridge element with HBMS(Highway Bridge Management System) data and In-depth Inspection Results by the survival analysis probability model. We developed the method that predicted cost of maintenance in all of the highway bridge in korea considering a characteristics of failures.

The number of highway bridge has been doubled for last 10 years. It is because many new highway routes has been completed since 2000. As a result, the maintenance cost of highway bridge has been increased as well. Therefore, to predict the long-term maintenance costs, there is a need for a method. To solve this problem, various studies about the life cycle cost analysis was conducted. Maintenance costs for members of the highway bridge is quite different to each other. Therefore, all the elements that are managed by the same proportion is inefficient. In this study, the distribution characteristics of maintenance costs for members of the highway bridge were analyzed using research data and highway bridge maintenance system data.

This paper presents the results of a life-cycle cost (LCC) analysis to select an efficient maintenance action for a deteriorated waterfront structure. Three different maintenance actions, a routine maintenance and two types of rehabilitation methods, were assumed and the corresponding the LCCs were calculated using a LC activity profile. The results of the analysis indicate that the LCC analysis can be effectively used to examine the maintenance alternative actions during the decision making process.

생애주기비용을 고려한 교량의 설계 및 유지관리에 있어서, 점검진단, 보수보강 등에 소요되는 직접적인 비용뿐만 아니라 간접적인 비용인 도로이용자비용은 중요한 비용항목으로 고려되고 있다. 직접비용과 비교하여 상대적으로 추정이 곤란한 도로이용자비용의 추정을 위하여 우회도로의 효과를 고려한 이용자지연비용과 차량운행비용의 정식화를 수행하고, 시간지체에 따른 도로이용자비용의 추정을 위한 회귀모델 개발을 위하여 교통해석과 회귀분석을 수행하였다. 개발된 회귀모델을 생애주기 비용 및 성능 기반 유지관리 전략 수립에 적용하여 도로이용자비용이 생애주기분석에 미치는 영향을 분석하고, 개발된 모델의 적용성에 대해서 고찰하였다. 도로이용자비용은 생애주기분석에 기초한 유지관리전략수립에 큰 영향을 미치며, 개발된 회귀모델은 교량의 도로이용자비용의 추정에 실용적으로 활용될 수 있을 것으로 판단된다.

본 연구에서는 생애주기비용을 고려한 성능기반 최적 유지관리 전략 수립 시스템을 개발하였다. 교량 수명동안 비용과 성능이라는 상반되는 목적을 균형있게 만족시킬 수 있는 유지관리 시나리오의 생성을 다중목적 조합최적화 문제로 정식화하고 유전자알고리즘을 적용하였다. 개발된 프로그램을 이용하여 국도 상 강거더 교량의 최적 유지관리 시나리오를 제공하는 과정을 제시하였다. 개발된 시스템은 현재의 교량 유지관리 전략 수립의 방법을 개선하여 교량 관리주체에게 다양한 제약 및 요구조건에 부합하는 최적의 교량 유지관리 시나리오를 제공할 수 있는 효율적인 도구로 활용될 수 있을 것으로 판단된다.