• 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.

• 한국국방경영분석학회지
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• 제22권2호
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• pp.153-165
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• 1996

This paper presents an order releasing algorithm for an AMS. Order release policy determine order releasing time to shop floor so as to improve order management and shop performance. The proposed order releasing algorithm can cope with the dynamic environment of orders(e.g. change or cancel of order) flexibly and fastly, by processing individual order and exchanging the information(e.g. compeletion time or lateness of order, etc) with customer. And the objective of the order releasing algorithm is the observance of the due-date, therefore, it can provide customer with a reliability of order. Computer simulation is used to obtain the makespan of order which is the input data of the order releasing algorithm. The eight candidate part dispatching rules are simulated to selected an effective part dispatching rule for the computer simulation. By using the best effective part dispatching rule, the computer simulation is conducted to determine order releasing time.

• 한국경영과학회지
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• 제24권2호
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• pp.1-15
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• 1999

This research involves the development and evaluation of a work flow control model for a type of flexible manufacturing system(FMS) called a flexible flow line(FFL). The control model can be considered as a kind of hybrid intelligent model in that it utilizes both computer simulation and neural network technique. Training data sets were obtained using computer simulation of typical FFL states. And these data sets were used to train the neural network model. The model can easily incorporate particular aspects of a specific FFL such as limited buffer capacity and dispatching rules used. It also dynamically adapts to system uncertainty caused by such factors as machine breakdowns. Performance of the control model is shown to be superior to the random releasing method and the Minimal Part Set(MPS) heuristic in terms of machine utilization and work-in-process inventory level.

• 한국농공학회논문집
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• 제54권5호
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• pp.17-24
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• 2012

The main purposes of the agricultural reservoir enlargement (ARE) project are to secure water supply reliability (WSR) for agriculture and to release environmental water during dry seasons. In this study, an operational rule that will simultaneously satisfy both the above issues was developed. Initial amount of water storage at the beginning of non-irrigation season (1st October) was divided into 3 stages, and the target level of water storage at the beginning of irrigation seasons (1st April) was set up. Required operational curves and release amounts were estimated based on the stages and target water levels. To evaluate the applicability of this rule, the amount of water released for environmental purposes and WSRs were analyzed for three reservoirs (Unam, Jangchi and Topjeong). The ratio between annual amount of release and additional amount of water storage were 1.6, 1.85, and 4.1 for the Unam, Jangchi, Tapjeong reservoirs, respectively. Also, the WSRs of all reservoirs were found to become higher than when the design standard was applied. Therefore, it is considered that the proposed rule is more suitable for the enlarged agricultural reservoirs operation as it satisfies the WSRs while securing the environmental water release.