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Supervisory control and data collection policies for a distribution center modeled as a discrete event system

机译:建模为离散事件系统的配送中心的监督控制和数据收集策略

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A large scale discrete event model of a distribution center is presented where critical parameters identified were utilized to create a real-time scheduling control policy to improve throughput and redistribute work in process (WIP), reducing bottleneck process and overall WIP. In implementing the control policy, it was found that the data was queried multiple times at the same time stamp and continuously throughout the process during a time when the control policy specification would not be met. The amount of data collection, processing and storage can become expensive especially when implementing multiple control policies that are dependent on several critical parameters. There is a need for smart data collection, processing and storage policies for cost effectiveness and to manage existing power management and battery life issues that may occur with continuous data streaming with existing wireless devices and sensors. This paper presents both the real-time scheduling control policy and the data collection policy for a distribution center that must be considered simultaneously in order to realize the maximum benefits of a wireless real-time scheduling system.
机译:提出了配送中心的大规模离散事件模型,其中使用确定的关键参数来创建实时调度控制策略,以提高吞吐量并重新分配在制品(WIP),从而减少瓶颈过程和总体WIP。在实施控制策略时,发现在同一时间标记处多次查询数据,并且在无法满足控制策略规范的时间内,在整个过程中连续查询数据。数据收集,处理和存储的数量可能变得昂贵,尤其是在实施依赖于几个关键参数的多个控制策略时。需要智能数据收集,处理和存储策略,以实现成本效益并管理现有电源管理和电池寿命问题,这些问题可能在使用现有无线设备和传感器进行连续数据流传输时发生。本文提出了配送中心的实时调度控制策略和数据收集策略,必须同时考虑这些策略,以实现无线实时调度系统的最大利益。

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