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首页> 外文期刊>Journal of Industrial Engineering and Management >A production throughput forecasting system in an automated hard disk drive test operation using GRNN
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A production throughput forecasting system in an automated hard disk drive test operation using GRNN

机译:使用GRNN在自动硬盘驱动器测试操作中的生产吞吐量预测系统

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Purpose: The goal of this paper is to develop a pragmatic system of a production throughput forecasting system for an automated test operation in a hard drive manufacturing plant. The accurate forecasting result is necessary for the management team to response to any changes in the production processes and the resources allocations.Design/methodology/approach: In this study, we design a production throughput forecasting system in an automated test operation in hard drive manufacturing plant. In the proposed system, consists of three main stages. In the first stage, a mutual information method was adopted for selecting the relevant inputs into the forecasting model. In the second stage, a generalized regression neural network (GRNN) was implemented in the forecasting model development phase. Finally, forecasting accuracy was improved by searching the optimal smoothing parameter which selected from comparisons result among three optimization algorithms: particle swarm optimization (PSO), unrestricted search optimization (USO) and interval halving optimization (IHO).Findings: The experimental result shows that (1) the developed production throughput forecasting system using GRNN is able to provide forecasted results close to actual values, and to projected the future trends of production throughput in an automated hard disk drive test operation; (2) An IHO algorithm performed as superiority appropriate optimization method than the other two algorithms. (3) Compared with current forecasting system in manufacturing, the results show that the proposed system’s performance is superior to the current system in prediction accuracy and suitable for real-world application.Originality/value: The production throughput volume is a key performance index of hard disk drive manufacturing systems that need to be forecast. Because of the production throughput forecasting result is useful information for management team to respond to any changing in production processes and resources allocation. However, a practically forecasting system for production throughput has not been described in detail yet. The experiments were conducted on a real data set from the final testing operation of hard disk drive manufacturing factory by using Visual Basics Application on Microsoft Excel? to develop preliminary forecasting system on testing and verification process. The experimental result shows that the proposed model is superior to the performance of the current forecasting system.
机译:目的:本文的目的是开发一种实用的生产量预测系统,用于硬盘驱动器制造厂中的自动化测试操作。准确的预测结果对于管理团队响应生产过程和资源分配中的任何变化都是必需的。设计/方法/方法:在本研究中,我们设计了硬盘制造中自动测试操作中的生产吞吐量预测系统厂。在提出的系统中,包括三个主要阶段。在第一阶段,采用互信息方法选择预测模型中的相关输入。在第二阶段,在预测模型开发阶段实施了广义回归神经网络(GRNN)。最后,通过从三种优化算法的比较结果中选择最优的平滑参数来提高预测精度,这三种优化算法是粒子群优化(PSO),无限制搜索优化(USO)和间隔减半优化(IHO)。结果:实验结果表明: (1)使用GRNN开发的生产吞吐量预测系统能够提供接近实际值的预测结果,并能够在自动硬盘驱动器测试操作中预测生产吞吐量的未来趋势; (2)IHO算法比其他两种算法具有优越性。 (3)与制造中的当前预测系统相比,结果表明该系统的预测精度优于当前系统,适合实际应用。原始性/价值:生产能力是生产能力的关键指标需要预测的硬盘驱动器制造系统。由于生产吞吐量的预测结果对于管理团队应对生产过程和资源分配中的任何变化提供了有用的信息。然而,尚未详细描述用于生产吞吐量的实际预测系统​​。通过使用Microsoft Excel上的Visual Basics Application,对硬盘驱动器制造工厂的最终测试操作中的真实数据集进行了实验。开发测试和验证过程的初步预测系统。实验结果表明,该模型优于目前的预测系统。

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