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首页> 外文期刊>International Journal of Computer Integrated Manufacturing >Integration of simulation and neural network in forecasting the throughput for TFT-LCD colour filter fabs
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Integration of simulation and neural network in forecasting the throughput for TFT-LCD colour filter fabs

机译：仿真和神经网络的集成来预测TFT-LCD彩色滤光片工厂的产能

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摘要

In manufacturing industry, the strategy of operations management influences the performance of production. The work in process control and order release policy are two important factors that would affect a decision-making of strategy. To evaluate the performance of these factors, simulation has been widely applied in recent years. Since running simulation always takes time, it is difficult to provide information promptly for production planners to respond to practical situation in industry. To solve this issue, a simulation assisted neural network forecasting system of throughput for thin film transistor liquid crystal display colour filter fabs is developed. This system enables planners to conduct what-if analysis for the production control policies without disturbing operations in a real plant. The obtained results show the forecasting system has the same capacity to estimate the throughput of production as a simulation model, but the response time is much faster.
机译：在制造业中，运营管理策略会影响生产绩效。流程控制中的工作和订单下达策略是会影响战略决策的两个重要因素。为了评估这些因素的性能，近年来仿真已广泛应用。由于运行模拟总是要花费时间，因此很难为生产计划人员及时提供信息以响应行业实际情况。为了解决这个问题，开发了一种用于薄膜晶体管液晶显示器彩色滤光片工厂的吞吐量的模拟辅助神经网络预测系统。该系统使计划人员可以对生产控制策略进行假设分析，而不会干扰实际工厂中的操作。所获得的结果表明，该预测系统具有与模拟模型相同的估计生产量的能力，但是响应时间要快得多。

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