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임동순(D. S. Yim),박찬현(C. H. Park),조남찬(N. C. Cho),오현승(H. S. Oh) 한국산업경영시스템학회 2009 한국산업경영시스템학회지 Vol.32 No.3
This paper introduces a case study for efficient generation of production schedules in a tube manufacturing system. The considered scheduling problem consists of two sub problems : lot sizing for a job and job sequencing. Since these problems require simulation optimization in which the performance measures are obtained by simulation execution, the trade-off between solution quality and computation time is an important issue. In this study, the optimal lot size for every product type is determined from simulation experiments. Then, target production quantity for each product type is transformed to several jobs such that a job consists of determined lot size. To obtain the good solution for a job sequence in a reasonable time, a number of alternatives are generated from heuristic rules developed by intuition and analysis of the considered system, and a job sequence is selected from simulation experiments.
오현승(H S Oh),김종수(C S Kim),이한교(H K Rhee),임동순(D S Yim),조진형(J H Cho) 한국산업경영시스템학회 2009 한국산업경영시스템학회지 Vol.32 No.4
In a technological driven environment, a depreciation estimate which is based on traditional like analysis results in a decelerated rate of capital recovery This time pattern of technological growths models needs to be incorporated into life analysis framework especially in those industries experiencing fast technological changes The approximation technique for calculating the variance can be applied to the six growth models that were selected by the degree of skewness and the transformation of the functions For the Pearl growth model, the Gompertz growth model, and the Weibull growth model, the errors have zero mean and a constant variance over time However, transformed models like the linearized Fisher-P교 model, the linearized Gompertz growth model, and the linearized Weibull growth model have increasing variance from zero to that point at which inflection occurs It can be recommended that if the variance of error over time is increasing, than a transformation of observed data is appropriate