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Augmenting an inbound raw material handling system of a steel plant by uncovering hidden logistics capacity

机译:通过发现隐藏的物流能力来增强钢铁厂的入库原料处理系统

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This paper presents an approach for inbound logistics capacity design by uncovering the hidden capacities of a raw material handling system of an integrated steel plant. The traditional analytical approach to capacity augmentation overlooked the possibility of capacity extraction from the existing system which resulted in sub optimal capacity design affecting capital investments and operational expenditures. Using discrete event simulation, we designed a capacity augmentation mechanism which would seek to maximize the utilization of unloading equipments, address system wide congestion and bottlenecks, and better the route layout resulting in released capacity while promoting seamless material flow. Our recommendation included changes in operational procedures, rearrangement of rake scheduling mechanisms, redesigned route network and equipment layout coupled with modest addition of unloading capacity. Our simulation model also showed significant reduction in operations cost through congestion management in the railway networks which resulted in superior ROIs when compared to the traditional approach.
机译:本文通过揭示综合钢铁厂原料处理系统的隐藏容量,提出了一种进站物流容量设计的方法。传统的能力扩充分析方法忽略了从现有系统中进行容量抽取的可能性,这导致次优容量设计影响了资本投资和运营支出。通过使用离散事件模拟,我们设计了一种容量增加机制,该机制将寻求最大程度地利用卸货设备,解决系统范围内的拥堵和瓶颈,并改善路线布局以释放容量,同时促进无缝物料流。我们的建议包括操作程序的更改,耙架调度机制的重新布置,重新设计的航线网络和设备布局以及适度增加的卸载能力。我们的仿真模型还显示,通过铁路网络中的拥塞管理,运营成本显着降低,与传统方法相比,可带来更高的投资回报率。

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