The dynamic transfer batch-size decision for thin film transistor-liquid crystal display array manufacturing by artificial neural-network
The dynamic transfer batch-size decision for thin film transistor-liquid crystal display array manufacturing by artificial neural-network
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DOI：
10.1016/j.cie.2011.01.012
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发表时间：
2011-05
期刊：
影响因子：
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通讯作者：
Taho Yang;Y. Shen
中科院分区：
文献类型：
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作者：
Taho Yang;Y. Shen
在薄膜晶体管-液晶显示器（TFT-LCD）的制造工艺中，阵列制造是一个重要的工艺。在阵列制造中，由于任务频繁，运输活动是一个重要的因素。阵列制造中的运输活动由自动化物料搬运系统（AMHS）完成。自动导向车辆（AGV）是用于运输储存在盒式玻璃基板的运输工具。盒式磁带的容量称为传输批量大小。先前对传输批大小决策的研究已经解决了一种最优方法，其中一个最优传输批大小假设具有已知条件。然而，在多变的生产环境中，可能存在多种传输批大小。因此，我们提出了在不稳定的生产环境中使用动态传输批大小策略的应用。为了获得适合当前生产环境的传输批大小，我们采用基于神经网络的方法作为决策机制的核心。该机制能够确定合适的传输批次大小，以便在当前生产环境的多种条件下进行有效和高效的运输。在实际应用中，将该方法与固定传输批大小策略进行了比较。结果表明，动态输送批量优于固定批量输送。
In the thin film transistor–liquid crystal display (TFT–LCD) manufacturing process, array manufacturing is an important process. Transporting activities in array manufacturing are an important factor because of the frequent tasks. The transporting activity in array manufacturing is performed by an automated material handling system (AMHS). Automated guided vehicle (AGV) is the transporter used to carry glass substrates that are stored in a cassette. The capacity of a cassette is known as the transfer batch-size. Prior research of decisions in transfer batch-size, has addressed an optimal methodology, where one optimal transfer batch-size is assumed to have known conditions. However, in the volatile production environment, there may be multiple kinds of transfer batch-sizes. Therefore, we present an application of using a dynamic transfer batch-size strategy within a volatile production environment. In order to obtain the appropriate transfer batch-size for the current production environment, we adopt a neural-network based methodology as the core of the decision-making mechanism. This mechanism has the capability to identify the suitable transfer batch-size to allow an effective and efficient transportation under numerous conditions within the current production environment. This methodology is compared with the fixed transfer batch-size strategy in a real practical case. The results show that the dynamic transfer batch-size is superior to the fixed batch-size transportation.