物联网环境下面向成品入库物流的叉车任务优化分配系统

发布时间：2018-07-20 09:48

【摘要】：在制造企业中,为确保产成品顺利向市场输出,企业在保证车间的连续生产的前提下,也要确保成品仓库的存储能力及周转效率。其中,成品入库物流的优化就成为重要的问题,即如何安排各车间下线点缓存区的托盘进行入库。而叉车作为运输托盘入库最重要的资源,其任务的优化分配显得尤为重要。本文针对广东X涂料制造企业的成品入库流程进行研究。在该企业中,叉车需要将产生于车间的成品及时送入成品仓并放在正确的库位。由于车间和仓库的数量较多,所有叉车将频繁的在多个车间和仓库之间往返,对叉车任务的分配存在诸多难点。第一,在成品运输入库的整个过程中缺少高效的识别方式,造成叉车操作员只能通过记忆和经验来操作入库,这样不仅费时费力,且易错遗漏,大大降低数据采集的准确性、高效性：第二,叉车车队管理者没有很好的对叉车任务分配的机制,只能通过人为的经验来安排叉车的运输任务,导致整体任务完成的效率低下。以上两个难点造成有些生产车间下线点缓存区堆满以至于不能连续生产,仓库的库位规划比较混乱,进而影响整个企业的成本和企业竞争力。物联网技术的自动采集信息、对物品实时监控和信息共享等特点为实现制造企业内部叉车任务的优化分配带来了契机。本文选用物联网技术解决叉车运输过程中信息采集难的问题,并以采集的实时数据为基础进行叉车任务的优化分配问题的研究。首先,针对制造企业中各车间生产下线、仓库库位规划和叉车运输作业的运作模式特点,分析叉车运输作业的关键问题,采用物联网技术对叉车运输作业资源进行透明化改造,并搭建了基于物联网的叉车运输作业环境和AUTOM实时基础信息架构。其次,对于制造企业成品入库物流运作中的叉车任务优化分配问题,提出了物联网环境下的动态任务分配机制,建立了任务排序的数学模型,并设计了遗传算法进行求解。最后,设计和开发了基于物联网的成品物流管理系统中的叉车任务优化分配模块。该模块采用B/S架构,并将叉车任务优化分配的机制应用于该模块的核心功能——自动任务分配中,实现了生产过程中叉车任务的动态优化分配。该系统已在广东X涂料制造企业运行,且对该企业的车间和仓库在效率上带来了明显的提高,各车间的连续生产率提高到了95%以上,仓库库位得到了快速释放周转,平均每单库存占用时间减少20%以上。
[Abstract]:In manufacturing enterprises, in order to ensure the smooth export of finished products to the market, enterprises should ensure the storage capacity and turnover efficiency of the finished goods warehouse on the premise of ensuring the continuous production of the workshop. Among them, the optimization of inventory logistics becomes an important problem, that is, how to arrange the trays in the buffer area of each workshop. Forklift truck as the most important resource of transport tray storage, its task allocation is particularly important. In this paper, the storage process of finished products in Guangdong X paint manufacturing enterprises is studied. In this enterprise, the forklift truck needs to put the finished products produced in the workshop into the finished goods warehouse in time and in the correct storage position. Due to the large number of workshops and warehouses, all forklifts will commute frequently between workshops and warehouses, so there are many difficulties in the assignment of forklift tasks. First, there is a lack of efficient identification in the whole process of transportation and storage of finished products, which results in forklift truck operators operating the warehouse only through memory and experience, which not only takes time and effort, but also is prone to errors and omissions, thus greatly reducing the accuracy of data collection. High efficiency: second, forklift fleet managers do not have a good mechanism for the task allocation of forklifts, only through artificial experience to arrange forklift transport tasks, resulting in the overall task of the completion of the efficiency is low. The above two difficulties cause the buffer area of the next line point in some production workshops to be piled up so that it can not be produced continuously and the warehouse location planning is rather confused which will affect the cost and competitiveness of the whole enterprise. The characteristics of the Internet of things (IoT) technology, such as automatic collection of information, real-time monitoring of goods and information sharing, bring an opportunity to optimize the distribution of forklift tasks in manufacturing enterprises. In this paper, the problem of information collection in forklift transportation is solved by using the technology of Internet of things, and the optimal allocation of forklift task is studied on the basis of the real-time data collected. First of all, according to the characteristics of production off-line, warehouse location planning and operation mode of forklift transportation in manufacturing enterprises, the key problems of forklift transportation operation are analyzed, and the transparent transformation of forklift transportation resources is carried out by using Internet of things technology. And build a forklift truck transportation environment and AUTOM real-time basic information architecture based on the Internet of things. Secondly, for the task optimization of forklift truck in the logistics operation of finished product storage, the dynamic task allocation mechanism under the environment of the Internet of things is put forward, the mathematical model of task ranking is established, and genetic algorithm is designed to solve the problem. Finally, the task optimization module of forklift in the finished product logistics management system based on Internet of things is designed and developed. This module adopts B / S architecture, and applies the mechanism of optimal task allocation of forklift truck to the automatic task assignment, which is the core function of the module, and realizes the dynamic optimal assignment of forklift task in the production process. The system has been running in Guangdong X paint manufacturing enterprise, and has brought about obvious improvement to the efficiency of the workshop and warehouse of this enterprise. The continuous productivity of each workshop has been increased to more than 95%, and the warehouse position has been rapidly released from turnover. Average inventory occupancy per unit reduced by more than 20%.
【学位授予单位】：广东工业大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TB497;TP391.44;TN929.5

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