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.

Fish mortality is the most important success factor in aquaculture management. To analyze the effect of mortality considering biological and economic condition is a important problem in land-based aquaculture. This study is aimed to analyze the effect of mortality for duration of cultivation in land-based aquaculture. This study builds the mathematical model that finds the value of decision variable to minimize cost that sums up the water pool usage cost, sorting cost, fingerling cost and feeding cost under critical standing corp constraint. The proposed mathematical model involves many aspects, both biological and economical: (1) number of fingerlings (2) timing and number of batch splitting event, based on (3) fish growth rate, (4) mortality, and (5) several farming expense. Numerical simulation model presented here in. The objective of numerical simulation is to provide for decision makers to analyse and comprehend the proposed model. When extensive biological and cost data become available, the proposed model can be widely applied to yield more accurate results.

The objective of this study is to examine the potential of cost reduction and factors affecting production cost of Korean farmers. First, the study estimates technical efficiency, allocation efficiency, and cost efficiency of Korean farmers using DEA. Then, Tobit regressions are conducted to identify factors affecting each of the three efficiency scores. The study uses the Farm Household Economy Survey data from the Korean National Bureau of Statistics for the period from 2008 to 2012. Results from DEA show that overall, technical and cost efficiency scores are low, which suggests a great potential of cost reduction for Korean farmers. The results also show relatively large differences in efficiency scores across provinces. Tobit results suggest that farm size, number of family members, operation costs, and invested capital amount are major factors affecting farm efficiencies.

일반국도유지보수 의사결정지원시스템에는 DB 이외에 1)포장상태지표의 공용성 모형, 2)포장상태지표 기반의 차량주행속도모형, 3)경제성 분석 모형과 4)의사결정지원 모형으로 구성된다. 특히 국토교통부의 「교통시설 투자지침서」에서 제시하는 도로이용자 및 사회·환경비용은 모두 차량운행속도의 함수로 구성되어있기 때문에 신뢰성 있는 차량운행속도모형의 개발이 요구된다. 즉, 도로의 상태기반 주행속도모형은 도로 부문의 편익 비용 항목 중 1)통행시간비용, 2)차량운행비용, 3)대기오염 비용, 4)온실가스비용, 5)소음비용 항목 등 이용자 비용 산정에 활용된다. 본 연구에서는 포장상태가 차량주행속도의 변수로 포함되도록 모형화 하는 것이 핵심이다. 먼저 유지보수 전·후의 『포장상태-차량속도』자료를 확보하기 위해 NC-200을 통해 현장조사를 실시하였다. 순창, 제천, 단 양, 증평의 네 구간을 선정하여 각 구간의 지형 분석, 교통량 측정 및 특성 분석을 실시하였다. 필터링 된 속도 자료를 활용하여 유지보수 전·후의 속도 차이를 AD(Anderson-Darling) 검정, t 검정, Mann-Whitney U 검정을 통해 통계적 유의성을 검정하였다. 모형개발을 위해 통계적 유의성이 검증된 구간 및 아스팔트 포장구간의 속도자료를 활용하여 표 1과 같이 모형을 개발하였다. 연구결과, 승용차를 대상으로 제한속도가 60km/h, 80km/h인 경우의 평지를 대상으로 한 모형구축 과정을 통해 세 가지 도로 상태(균열, 소성변형, IRI)별 속도는 통계적으로 유의한 차이가 있음을 확인하였다. 개발된 속도모형을 통해 도로 이용자비용의 산출이 가능하며 향후 일반국도유지보수 의사결정지원시스템의 경제성 분석 및 유지보수 대상구간의 우선순위 결정 등 다양하게 활용가능하리라 기대된다.

Previous researches have focused on the efficiency of project execution and the satisfaction of internal customers in view of the fact that a project is successful if any defects are not found in the short-term performance test of the project final outcom

Recently many researchers contributed to the understanding of Quality Control System, but the use of economics in the design of quality assurance system is limited in treatment of the relationship between the average incoming quality level (or average process quality level) of the incoming lot and the average outgoing quality level of this lot. In this study, a traditional concept of sampling inspection plan for the quality assurance system is extended to a consideration of economic aspects in total production system by representing and analyzing the effects between proceeding and succeeding production process including inspection process. This approach recognizes that the decision at each manufacturing process (or assembly process), is to be determined not only by the cost and the average outgoing quality level of that process, but also by the input parameters of the cost and the incoming quality to the succeeding process. By analyzing the effects of the average incoming and outgoing quality, manufacturing or assembly process quality level and sampling inspection plan on the production system, mathematical models and solution technique to minimize the total production cost for a general product manufacturing system with specified average outgoing quality limit are suggested.

This paper presents an analytic method of quality function deployment(QFD) that is to maximize customer satisfaction subject to technical and economic sides in process design. We have used Wasserman's normalization method and the analytical hierarchy process(AHP) to determine the intensity of the relationship between customer requirements and process design attributes. This paper also shows cost-quality model the tradeoff between quality and cost as a linear programming(LP) with new constraints that have designated special process required allocating firstly. The cost-quality function deployment of piston ring is presented to illustrate the feasibility of such techniques.

This paper presents an analytic method of quality function deployment(QFD) that is to maximize customer satisfaction subject to technical and economic sides in process design. We have used Wasserman's normalization method and the analytical hierarchy process(AHP) to determine the intensity of the relationship between customer requirements and process design attributes. This paper also shows cost-quality model the tradeoff between quality and cost as a linear programming(LP) with new constraints that have designated special process required allocating firstly The cost-quality function deployment of piston ring is presented to illustrate the feasibility of such techniques.

본 연구는 도시 우수관망 설계 시 주어진 설계유량을 효율적이고 경제적인 단면 구성과 관망에 따른 우수배제 능력을 극대화시키기 위해 최적화 기법인 동적계획법(Dynamic Programming : DP)의 특수한 방법인 이산미분형 동적계획법(Discrete Differential Dynamic programming DDDP)를 이용해 최적화된 설계조건을 구할 수 있도록 하였다. 이산미분형 동적계획법의 기법은 설계유량과 맨홀의 위치가 결정되면 그에 따른 최

본 연구는 도시 우수관망 설계 시 주어진 설계유랑을 효율적이고 경제적인 단면 구성과 관망에 따른 우수배제능력을 극대화시키기 위해 최적화된 설계를 통하여 경제적인 우수시스템을 설계할 수 있는 모형의 개발이 이루어져야 할 필요성이 있다. 이에 본 연구에서는 최적화 기법으로 동적계획법(Dynamic Programming : DP)의 특수한 방법인 이산미분형 동적계획법(Discrete Differential Dynamic Programming : DDDP)를