• 한국건설관리학회논문집
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• 제8권4호
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• pp.203-213
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• 2007

In the past, several construction projects have exceeded their schedule resulting in financial losses to the owners; at present there are very few methods available to accurately forecast the completion date of a project. These nay be because of unforeseen outcomes that cannot be accounted for earlier and because of deficiency of proper tools to forecast completion date of said project. To overcome these difficulties, project managers may need a tool to predict the completion date at the early stage of project development. Bayesian Inference introduced in this paper is one such tool that can be employed to forecast project progress at all construction stages. Using this inference, project managers can combine an initially planned project progress (growth curve) with reported information from ongoing projects during the development, and in addition, dynamically revise this initial plan and quantify the uncertainty of completion date. This study introduces a theoretical model and proposes a mathematically information-based framework to forecast a project completion date that corresponds with the actual progress data and to monitor the modified uncertainties using Bayesian Inference.

• Industrial Engineering and Management Systems
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• 제2권1호
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• pp.9-27
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• 2003

In a wafer fabrication factory, the completion time of an order is affected by many factors related to the specifics of the order and the status of the system, so is difficult to predict precisely. The level of influence of each factor on the order completion time may also depend on the production system characteristics, such as the rules for releasing and dispatching. This paper presents a method to identify those factors that significantly impact upon the order completion time under various combinations of scheduling rules. Computer simulations and statistical analyses were used to develop effective due date assignment models for improving the due date related performances. The first step of this research was to select the releasing and dispatching rules from those that were cited so frequently in related wafer fabrication factory researches. Simulation and statistical analyses were combined to identify the critical factors for predicting order completion time under various combinations of scheduling rules. In each combination of scheduling rules, two efficient due date assignment models were established by using the regression method for accurately predicting the order due date. Two due date assignment models, called the significant factor prediction model (SFM) and the key factor prediction model (KFM), are proposed to empirically compare the due date assignment rules widely used in practice. The simulation results indicate that SFM and KFM are superior to the other due date assignment rules. The releasing rule, dispatching rule and due date assignment rule have significant impacts on the due date related performances, with larger improvements coming from due date assignment and dispatching rules than from releasing rules.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2017년도 춘계 학술논문 발표대회
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• pp.278-279
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• 2017

Result from Amendment of Apartment Houses Decree Customer Service, Recently, the starting point of Defects Liability changed "Criteria of Completion date" to "Delivery date to Divided property". Through the Law amended, There are some inconsistency between "Claim for repairing defects" and "Period of security deposit for repairing defects claim". If someone bought a house after Completion date, Purchasing period of "Claim to security deposit for repairing defects" lapsed without renewal. This research is to identify problems and solutions for improving the system.

• 한국경영과학회지
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• 제17권3호
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• pp.1-12
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• 1992

Parallel Genetic Algorithms (GAs) are developed to solve a single machine n-job scheduling problem which is to minimize the sum of absolute deviations of completion times from a common due date. (0, 1) binary scheme is employed to represent the n-job schedule. Two selection methods, best individual selection and simple selection are examined. The effect of crossover operator, due date adjustment mutation and due date adjustment reordering are discussed. The performance of the parallel genetic algorithm is illustrated with some example problems.

• 산업경영시스템학회지
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• 제29권2호
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• pp.7-12
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• 2006

This study considers the problem of scheduling jobs on uniform parallel machines with a common due date. The objective is to minimize the total absolute deviation of job completion times about the common due date. This problem is motivated by the fact that a certain phase of printed circuit board manufacturing is bottleneck and the processing speeds of parallel machines in this phase are uniformly different for all jobs. Optimal properties are proved and a simple polynomial time optimal algorithm is developed.

• Architectural research
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• 제10권1호
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• pp.41-48
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• 2008

Construction projects have frequently exceeded their schedule despite reliable estimates at the start of a project. This problem was attributed to unpredictable causes at the beginning and to shortage of proper tools to accurately predict project completion date. To supplement this difficulty, project managers need a comprehensive system that can be employed to monitor the progress of an ongoing project and to evaluate potential delay for achieving the goal on time. This paper proposed a progressive-based expert system for quantitative assessments of project delay at the early stages of the execution. Furthermore, the system is used to inspect the change of the uncertainty on completion date and its magnitude. The proposed expert system is helpful for furnishing project managers a warning signal as a project is going behind schedule and for tracking the changed uncertainty at a desired confidence level. The main objectives of this paper are to offer a new system to overcome the difficulties of conventional forecasting tools and to apply a construction project into the system to illustrate its effectiveness. This paper focuses on construction phase of project development and is intended for the use by project managers.

• 산업경영시스템학회지
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• 제14권23호
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• pp.27-36
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• 1991

This paper considers scheduling a set of n-jobs on m-paraller identical processors in which all jobs have the common due date. The objective of the problem is to minimize the weighted mean absolute deviation of job completion times about such common due dates under the assumption that each job has a different weight. and to determine the optimal value of a common due date. We propose four heuristic solution methods based on several dominance conditions, and its solution procedure is illustrated with numerical examples. The Performance comparison is made among four heuristic scheduling procedures.

• 한국작물학회지
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• 제55권3호
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• pp.259-267
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• 2010

This study was performed at Rice and Winter Cereal Crops Department of NICS during 2007 and 2008 to investigate the characteristics of rice leaf emergence and to obtain basic data which can be used for rice growth simulation model by which we can forecast rice growth stage and heading date accurately under different cultivars, transplanting date, and climatic conditions. To confirm leaf emergence rate according to rice maturing ecotype, we surveyed the leaf emergence rate and heading date of Unkwangbyeo, Hwayoungbyeo and Nampyeongbyeo which are early maturing, medium maturing and medium-late maturing cultivars, respectively, according to seedling raising duration and transplanting time. When seedling duration was 15 days, the growth duration between transplanting time and completion of flag leaf emergence on main culm were 51.5~78.3 days in Unkwangbyeo, 55.3~87.9 days in Hwayoungbyeo and 58.4~98.4 days in Nampyeongbyeo, respectively. When seedling duration was 30 days, they were 50.1~75.5 days in Unkwangbyeo, 52.4~84.7 days in Hwayoungbyeo and 56.4~93.8 days in Nampyeongbyeo, respectively. As transplanting time delayed, the emerged leaf number after transplanting decreased in all rice cultivars. The cumulative temperature between transplanting time to completion of flag leaf elongation on main culm were $1,281^{\circ}C{\sim}1,650^{\circ}C$ in Unkwangbyeo, $1,344^{\circ}C{\sim}1,891^{\circ}C$ in Hwayoungbyeo and $1,454^{\circ}C{\sim}2,173^{\circ}C$ in Nampyeongbyeo, respectively. Leaf emergence rate on main culm were precisely represented by equation, y = $y_0$ + a / [1 + exp( - (x - $x_0$) / b)]^c, when we used daily mean temperature as variable.

• 문화기술의 융합
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• 제5권3호
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• pp.43-54
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• 2019

이 연구는 아파트 화재의 대형화를 막기 위해 소방공사감리원의 업무수행능력에 따른 완공검사결과와 소방공사감리원의 성능시험 공기확보의 필요성에 따른 완공검사결과 및 완공검사증명서 발급 후 소방시설 등의 하자 유무상태에 따른 요인을 분석하여 완공검사 결과를 측정하여 소방공사감리원의 업무수행능력을 향상시키 위한 것이다. 연구의 결과를 요약하면 첫째, 소방공사감리원의 업무수행능력에 따라 아파트 완공검사결과에 영향을 미치는 것으로 직업별로 소방공무원보다 소방시설설계업 및 소방공사감리업 종사자가 소방공사감리원의 업무수행능력에 따라 아파트 완공검사 결과 정도는 유의하게 높게 나타났다. 그러므로 아파트에는 아파트 공사감리 경력이 있는 사람을 감리원으로 배치하여 소방공사감리원의 업무수행능력을 향상시킬 필요가 있다. 둘째, 소방공사감리원의 성능시험 공기확보 필요성에 대한 완공검사 결과는 직업별로 소방공무원보다 소방시설설계업 및 소방공사감리업 종사자의 성능시험에 대한 공기확보 필요성이 유의하게 높은 것으로 분석 되었다. 이를 개선하기 위해 건축 준공일까지 완공검사를 할 수 있도록 하며 발주처에서는 완공검사증명서를 건축준공일에 임박하여 발급받도록 강요하지 않도록 장치를 마련할 필요가 있다. 마지막으로, 완공검사증명서 발급 후 완공검사의 하자가 완공검사 결과에 영향을 미치는 것으로 발주자(건축주. 감독관) 종사자보다 소방시설설계업 및 소방공사감리업체 종사자가 유의하게 낮게 분석되었다. 이는 소방시설공사를 마치지 않은 상황에서 발주처. 건설사가 완공검사증명서의 발급을 요구함에 따라 완공검사증명서 발급 후 소방시설 등에 하자가 발생하여 완공검사 결과에 영향을 미친 것으로 분석된다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.844-847
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• 1997

In this paper, scheduling problem is dealt for the minimization of due date penalty for the customer order. Multiproduct batch processes have been dealt with for their suitability for high value added low volume products. Their scheduling problems take minimization of process operation for objective function, which is not enough to meet the customer satisfaction and the process efficiency simultaneously because of increasing requirement of fast adaptation for rapid changing market condition. So new target function has been suggested by other researches to meet two goals. Penalty function minimization is one of them. To present more precisely production scheduling, we develop new scheduling model with penalty function of earliness and tardiness We can find many real cases that penalty parameters are divergent by the difference between the completion time of operation and due date. That is to say, the penalty parameter values for the product change by the customer demand condition. If the order charges different value for due date, we can solve it with the due date period. The period means the time scope where penalty parameter value is 0. If we make use of the due date period, the optimal sequence of our model is not always same with that of fixed due date point. And if every product have due date period, due date of them are overlapped which needs optimization for the maximum profit and minimum penalty. Due date period extension can be enlarged to makespan minimization if every product has the same abundant due date period and same penalty parameter. We solve this new scheduling model by simulated annealing method. We also develop the program, which can calculate the optimal sequence and display the Gantt chart showing the unit progress and time allocation only with processing data.