英文翻译外文文献翻译43仓储控制堆垛系统，理论基础.docx
英文翻译外文文献翻译43仓储控制堆垛系统，理论基础
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英文翻译外文文献翻译43仓储控制堆垛系统，理论基础,机械毕业设计英文翻译
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1 附 录 Storage controlled pile-up systems, theoretical foundations Abstract： This paper presents the theoretical foundations for controlling pile-up systems. A pile-up system consists of one or more stacker cranes picking up bins from a conveyor and placing them onto pallets with respect to costumer orders. The bins usually arrive at a conveyor from an order picking system. We give a mathematical definition of the pile-up problem, define a data structure for control algorithms, introduce polynomial time algorithms for deciding whether a system can be blocked by making bad decisions, and show that the pile-up problem is in general NP-complete. For pile-up systems with a restricted storage capacity or with a fixed number of pile-up places the pile-up problem is proved to be solvable very efficiently. 1. Introduction A pile-up system usually consists of one or more stacker cranes which pick up bins from a conveyor and place them onto pallets. Vehicles take full pallets from pile-up places to trucks and bring new empty pallets to pile-up places. The conveyor at which the bins arrive is in general the back-end of an order picking system. To understand the problems involved when controlling pile-up systems we first sketch the operation mode of an order picking system. Most of our notations are adopted from 2 A customer order consists of a list of articles. The ordered articles have to be packed for delivery into bins of equal size. An order is divided into several order lists, one for each bin. The order list contains the articles and their quantities to be picked from shelf racks into the bin. Empty bins are placed at the beginning of a conveyor. A barcode containing the order list number is attached to each empty bin. The barcode is used to recognize automatically a bin at control positions. A common size of the bins is 60 cm 40 cm 35cm(1 w h). The conveyor transports the bins to the so-called picking stations. If some articles have to be picked at a picking station then the transportation system automatically pushes out the bin to a secondary conveyor. On the secondary conveyor the bin can be stopped nts 2 without blocking the flow of bins on the main conveyor. The picker gets information about the articles to pick by a visual display unit. He picks the indicated articles from the shelves and put them into the bin. Having finished the picking, the bin is pushed back onto the main conveyor. The main conveyor transports the bin to the next picking station, etc. The order picking systems we consider consist of a roller conveyor that cyclically connects all picking stations. A common conveyor speed is about 0.5 m/s. Fig. 1 sketches a top view of such an order picking system. The picking stations and shelf racks are located in the so-called commission area. Each secondary conveyor has only a small storage capacity for approximately three or four bins at each picking station. If a bin can not be pushed out because the secondary conveyor is completely occupied by bins, then the bin is transported to the next picking station or is going on moving on the main conveyor until it reaches the same station again. Such order picking systems are highly flexible in storage capacity as well as in picking capacity. The shelves can be divided into more slots to store more different products. More orders can be handled by simply bringing in more pickers. The capacity can be reduced by reducing the number of pickers and letting each picker handle several picking stations. Such order picking systems become more and more common by supply industry and warehouses in Germany and the Netherlands. In 2, de Koster models acyclic order picking systems as a network of connected conveyor pieces and picking stations. The aim of the modeling is, for a particular design, to provide fast information on throughput times of bins, picker utilization, and the average number of bins in the system. The analysis of the model is based on Jackson network analysis; see, for example. The queues of the network can also be analyzed as stand-alone M/M/c queues 2 by standard methods; see, for example, 6. If not all picking stations are occupied by pickers then some bins possibly have to wait at the secondary conveyor of a picking station until some picker comes to the idle station and picks the articles. If the secondary conveyor is full the bins have to cycle at the main conveyor. Such waiting situations influence the overall throughput of the system and usually rearrange the bins. This rearrangement could cause some trouble when bins have to be placed for delivery onto pallets. All bins belonging to one costumer order have to be placed onto the same pallet if possible. If the number of bins of an order exceeds the nts 3 capacity of a pallet then the order is divided into suborders of which each fit onto a pallet. A common maximal capacity of a pallet is about 32 bins, 4 bins side by side and 8 bins one upon the other. Additionally, each pallet has to contain a minimal number of bins. A common minimal capacity of a pallet is about 28 bins. If orders or suborders contain less than the minimal number of bins then they will be combined and piled up on a so-called mixed pallet. Such a combination is only allowed if the involved orders are destined for the same geographical region. The pile-up system is located at the end of an order picking system, where the bins have to be piled up onto pallets. Fig. 2 sketches the top view of a pile-up system. The bins arrive the pile-up system on the main conveyor of the order picking system. At the end of the main conveyor the bins enter a cyclic storage conveyor. At the storage conveyor bins are pushed out to buffer conveyors, where they are queued. Each buffer conveyor Bi is associated with a primary pile-up place Pi and a secondary pile-up place Qi. The bins in buffer conveyor Bi are destined for the pallets piled up on place P/or Qi. A stacker crane picks the stopped bin from the end of buffer conveyor Bi and place it onto the pallet located at primary place Pi. If a pallet is completely piled up, a vehicle brings it to a truck and moves a new empty pallet to the places. Unfortunately, the bins arrive the pile-up system not in a succession such that they can be placed one after the other onto pallets. If more places are needed then an incomplete pallet can temporarily be moved from a primary place Pi to a free secondary place Qi. However, if all primary places and all secondary places are occupied by incomplete pallets and the storage conveyor is completely filled with bins not destined for the pallets on the places, then the pile-up system is blocked. To unblock the system, bins of the storage conveyor have to be temporarily put on the floor or bins from the main conveyor have to be manually picked and brought to the pallets. Due to the additional extra costs, a blocking situation is a nightmare for each distribution company. Controlling a pile-up system means to make the right decision whenever a new pallet is piled up such that no blocking situation will arise. In this paper, we give the theoretical foundations for controlling such pile-up systems. The paper is organized as follows: In Section 2, we introduce the main notations and give a formal definition of the pile-up problem. We are basically interested in how to control a pile-up system such that no blocking situation arise. The time needed to execute the suggested actions is more or less nts 4 unimportant. Thus, in the formal definition, the possibility to use secondary places can be ignored. Secondary places can be handled like primary places, because the pallets on the places can be exchanged by the vehicle in the loading zone. Using buffer conveyors is also not essentially for the theoretical model, because bins can only be picked up from the end of the buffer conveyor and the bins in the buffer conveyor can not be rearranged. Thus stacker cranes could also pick up bins directly from the conveyor if this would technically be possible. In Section 3, we define the decision graph and show that each algorithm for controlling a pileup system has to solve an NP-complete problem. We also show that the question whether a system can be blocked by making bad decisions can be answered in polynomial time. In Section 4, we consider restricted pile-up systems in which the capacity of the storage conveyor is restricted or the number of pile-up places is fixed. We show that even parallel algorithms exist for controlling restricted pile-up systems. In Section 5, we discuss the possibility to form mixed pallets. Conclusions and discussions are given in Section 6. nts 5 仓储控制堆垛系统，理论基础 摘要 ： 本文提出了控制 堆垛 系统的理论基础。一 堆垛 系统由一个或多个堆垛 起重机组成 ，通过 传送带 把客户的订单放置在 托盘上。通常到达的 仓库通过 从一 拣货 系统 输送 。 我们给一个 堆垛 问题的数学定义，定义一个数据结构的控制算法，引入系统是否可阻断作出错误的决定，并表明 堆垛 问题在多项式时间算法的一般决定的 NP -完成。对于 堆垛系统 限制 性仓库 或者 部分的堆垛仓库的堆垛问题被证明是可解的 。 简介 ： 一堆积 系统通常由一个或多个堆垛起重机的捡起一箱及输送他们放到托盘。车辆从 装 的地点 装满 托盘车 带到 新的空货盘堆积的地点。输送带在哪个 仓库 到达一般 的 后备 装置的结束是一个拣货系统 .为了 了解涉及控制 堆积 系统 的问题时 ，我们首先勾勒出一个 拣货 系统的运作模式。我们的符号大部分是通过从 2。 客户订单由一个物品的清单。订购的物品都必须进入同样大小箱包装运送。命令分为几个命令列表，每一个 仓库 。该命令列表中包含的 物品 和它们的数量可从货架货架拿起扔进 仓库 。空箱被放置在一个传送带开始。条形码包含订单列表编号，贴在每个空箱。条形码是用来控制自动识别位置 1 桶。一个普通大小的回收箱是 60 厘米 40厘米 35 厘米（ 1 宽 高）。 输送带输送 货 箱 到 所谓的采摘站 点。 如果某些条款已被 采摘站采摘 ，然后在运输系统自动推到了 第二仓库 输送。在 第二 输送本可以不 堵塞 主要输送 方向 流 动 。在选择器获取有关的 物品 信息来选择是通过一种视觉显示装置。他从货架上挑选指定的 物品 ，把它们扔进 仓库 。 完成 采摘， 把货箱 推到主传送带。主要输送机运输到下一个车站采摘等 等。 我们考虑的 拣货 系 统包括一个辊子输送机连接所有的周期性复苏 站。 一个常见的输送速度约为 0.5 米 /秒 。 图 1， 勾划出一幅这样的 拣货 系统顶视图 。 采摘站和货架位于所谓的佣金地区。每 第二次 输送了大约三，四箱每个采摘站只有一小的存储容量。如果一 个货箱 不能推 动 ，因为 第二 输送机完全占领了 仓库 , 那么 货箱 采摘运到下一个站 点 或在主传送带上移动，直到 再次 达到 相同 的站 点 了。 这种 拣货 系统具有高度灵活的存储容量以及在采摘的能力。货架上可分为多插槽存储更多不同的产品。可以处理更多的订单，只需带来更多的采摘。容量可减少工人数量减少，并让每个拣货处理若干采摘站。这种 拣货 系统变得越来越常见的供应业和仓库在德国和荷兰。 nts 6 2，去科斯特模型作为连接件，采摘站输送网络无环 拣货 系统。该模型的目的是，为特殊设计，提供回收箱吞吐量倍，采摘利用快速的信息，并在系统中的箱平均数。该模型的分析是根据杰克逊网络分析，见，例如， 5。该网络的队列，也可以分析作为独立的 M / M /炭队列 2 标准方法 ;见，例如 ， 6。 如果不是所有采摘站占领了一些 仓库 可能要等一个站二次输送采摘一些涉及到空闲站和挑选的 物品 。如果辅助输送已满 载 在主传送带循环。这种等待的情况影响到系统的整体吞吐量，通常重新排列箱。这可能导致一些麻烦重排箱时必须放在托盘上。所有 仓库 属于一个负荷消费秩序， 如果 可能的话 放置 到同一托盘上。如果一项命令箱的数目超过了一托盘容量然后顺序分为亚目划分的，每个托盘上一个合适的。一个共同的一个托盘最大容量约为 32 箱， 4 箱 8 箱由方一方，另一方。此外，每个托盘必须包含箱最小数量。一个共同的一个托盘最小容量为 2
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