發(fā)布時間：2018-07-20 09:48

【摘要】：在制造企業(yè)中,為確保產成品順利向市場輸出,企業(yè)在保證車間的連續(xù)生產的前提下,也要確保成品倉庫的存儲能力及周轉效率。其中,成品入庫物流的優(yōu)化就成為重要的問題,即如何安排各車間下線點緩存區(qū)的托盤進行入庫。而叉車作為運輸托盤入庫最重要的資源,其任務的優(yōu)化分配顯得尤為重要。本文針對廣東X涂料制造企業(yè)的成品入庫流程進行研究。在該企業(yè)中,叉車需要將產生于車間的成品及時送入成品倉并放在正確的庫位。由于車間和倉庫的數量較多,所有叉車將頻繁的在多個車間和倉庫之間往返,對叉車任務的分配存在諸多難點。第一,在成品運輸入庫的整個過程中缺少高效的識別方式,造成叉車操作員只能通過記憶和經驗來操作入庫,這樣不僅費時費力,且易錯遺漏,大大降低數據采集的準確性、高效性：第二,叉車車隊管理者沒有很好的對叉車任務分配的機制,只能通過人為的經驗來安排叉車的運輸任務,導致整體任務完成的效率低下。以上兩個難點造成有些生產車間下線點緩存區(qū)堆滿以至于不能連續(xù)生產,倉庫的庫位規(guī)劃比較混亂,進而影響整個企業(yè)的成本和企業(yè)競爭力。物聯網技術的自動采集信息、對物品實時監(jiān)控和信息共享等特點為實現制造企業(yè)內部叉車任務的優(yōu)化分配帶來了契機。本文選用物聯網技術解決叉車運輸過程中信息采集難的問題,并以采集的實時數據為基礎進行叉車任務的優(yōu)化分配問題的研究。首先,針對制造企業(yè)中各車間生產下線、倉庫庫位規(guī)劃和叉車運輸作業(yè)的運作模式特點,分析叉車運輸作業(yè)的關鍵問題,采用物聯網技術對叉車運輸作業(yè)資源進行透明化改造,并搭建了基于物聯網的叉車運輸作業(yè)環(huán)境和AUTOM實時基礎信息架構。其次,對于制造企業(yè)成品入庫物流運作中的叉車任務優(yōu)化分配問題,提出了物聯網環(huán)境下的動態(tài)任務分配機制,建立了任務排序的數學模型,并設計了遺傳算法進行求解。最后,設計和開發(fā)了基于物聯網的成品物流管理系統中的叉車任務優(yōu)化分配模塊。該模塊采用B/S架構,并將叉車任務優(yōu)化分配的機制應用于該模塊的核心功能——自動任務分配中,實現了生產過程中叉車任務的動態(tài)優(yōu)化分配。該系統已在廣東X涂料制造企業(yè)運行,且對該企業(yè)的車間和倉庫在效率上帶來了明顯的提高,各車間的連續(xù)生產率提高到了95%以上,倉庫庫位得到了快速釋放周轉,平均每單庫存占用時間減少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%.
【學位授予單位】：廣東工業(yè)大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：TB497;TP391.44;TN929.5

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