播种式拣选技术在某大型医药配送中心的应用研究
发布时间：2018-08-07 11:14
【摘要】：在医疗卫生事业蓬勃发展的今天,国民对医疗健康的关注度整体提高,国家对医疗事业建设的投入也随之加大,加之,现代医疗自身水平的发展,医药行业朝着更加多样化与个性化的方向发展,这就要求医药企业通过对自身的完善来提高整个医疗市场的服务水平,同时医药的配送速度关系到病人的生命安危,所以要求医药配送中心能够更快的对订单做出反应,为顾客提供更及时的配送,因为医药的种类繁多,客户的个性化选择更多,订单也朝着中小批量转换,配送中心对分拣时效性的要求也越来越高,因此,本文通过对某医药配送中心的研究,将客户订单作为基本的研究方向。根据订单的特点匹配最优的拣选方式。本文首先对当前国内外医药配送中心的研究及发展状况进行简单介绍,同时对配送中心的拣选策略及订单的处理方式进行描述,对医药配送中心在整个医药供应链上得作用进行了介绍,然后对医药的拣选作业方式进行了区分,并将EIQ的分析引入到订单分析当中,将其分解为EQ、EN、IQ、IK四种分析方法。为了弥补在订单的品项构成和分布情况上的不足,本文又引入订单矩阵对订单及品项特点进行研究。将订单的行向量作为订单量,列向量作为品项,同时相应的加入了订单的订货频次及订单的单品数量。然后本文又在订单矩阵的基础上提出了聚类算法,使用帕累托曲线对订单及品项进行筛选,利用K-平均聚类对原有的订单矩阵进行品项及订单分析,然后生成最终的分类订单矩阵。将不同类型的订单及品项根据聚集簇进行划分,以此来明确配送中心的订单分析策略。为验证订单在聚类分析以及COI储位分析对于播种式拣选方式具有有效优化效果,将储位进行随机排列以及COI降序排列两种方式在双向旋转货架上进行货品的摆放。选取靠近中心簇的两组订单,通过播种式拣选的时间模型对两种排列方式进行仿真分析。对最终的拣选时间进行计算。该模型能够验证订单的聚类分析方法在储位优化上的有效性及可行性,在配送中心的规划上提供理论及现实的指导作用。
[Abstract]:Today, with the vigorous development of medical and health care, people's attention to medical and health has been raised as a whole, and the state's investment in the construction of medical services has also increased. In addition, the development of modern medical care itself has also increased. The pharmaceutical industry is developing towards a more diversified and individualized direction, which requires pharmaceutical enterprises to improve the service level of the whole medical market by perfecting themselves. At the same time, the distribution speed of medicine is related to the lives of patients. So the medical distribution center should be able to respond to orders more quickly and provide customers with more timely delivery, because of the wide variety of medicines, the more individualized choices of customers, and the transition of orders to medium and small batches. The requirement of sorting timeliness in distribution center is more and more high. Therefore, through the research of a medical distribution center, the customer order is regarded as the basic research direction in this paper. Match the optimal selection method according to the characteristics of the order. In this paper, the current research and development of medical distribution centers at home and abroad are briefly introduced. At the same time, the selection strategy and order processing methods of distribution centers are described. This paper introduces the role of medical distribution center in the whole pharmaceutical supply chain, and then distinguishes the picking operation mode of medicine, and introduces the analysis of EIQ into order analysis, and decomposes it into four analytical methods: EQN, IQN, IQIK. In order to make up for the deficiency in the composition and distribution of order items, this paper introduces the order matrix to study the characteristics of orders and items. The order line vector is taken as the order quantity, the column vector is taken as the item, and the order frequency and the order quantity are added accordingly. Then, based on the order matrix, a clustering algorithm is proposed. The Pareto curve is used to screen the order and its items, and the K- average clustering is used to analyze the items and orders of the original order matrix. Then the final classification order matrix is generated. Different types of orders and items are divided according to the cluster to determine the order analysis strategy of the distribution center. In order to verify the effectiveness of order clustering analysis and COI storage analysis for seeding sorting, the storage locations were randomly arranged and the COI descending order was arranged on the two-way rotating shelves. Two groups of orders close to the central cluster were selected and simulated by seeding time model. Calculate the final picking time. The model can verify the validity and feasibility of the order clustering analysis method in the storage optimization, and provide theoretical and practical guidance in the planning of distribution center.
【学位授予单位】：昆明理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F252;F426.72
[Abstract]:Today, with the vigorous development of medical and health care, people's attention to medical and health has been raised as a whole, and the state's investment in the construction of medical services has also increased. In addition, the development of modern medical care itself has also increased. The pharmaceutical industry is developing towards a more diversified and individualized direction, which requires pharmaceutical enterprises to improve the service level of the whole medical market by perfecting themselves. At the same time, the distribution speed of medicine is related to the lives of patients. So the medical distribution center should be able to respond to orders more quickly and provide customers with more timely delivery, because of the wide variety of medicines, the more individualized choices of customers, and the transition of orders to medium and small batches. The requirement of sorting timeliness in distribution center is more and more high. Therefore, through the research of a medical distribution center, the customer order is regarded as the basic research direction in this paper. Match the optimal selection method according to the characteristics of the order. In this paper, the current research and development of medical distribution centers at home and abroad are briefly introduced. At the same time, the selection strategy and order processing methods of distribution centers are described. This paper introduces the role of medical distribution center in the whole pharmaceutical supply chain, and then distinguishes the picking operation mode of medicine, and introduces the analysis of EIQ into order analysis, and decomposes it into four analytical methods: EQN, IQN, IQIK. In order to make up for the deficiency in the composition and distribution of order items, this paper introduces the order matrix to study the characteristics of orders and items. The order line vector is taken as the order quantity, the column vector is taken as the item, and the order frequency and the order quantity are added accordingly. Then, based on the order matrix, a clustering algorithm is proposed. The Pareto curve is used to screen the order and its items, and the K- average clustering is used to analyze the items and orders of the original order matrix. Then the final classification order matrix is generated. Different types of orders and items are divided according to the cluster to determine the order analysis strategy of the distribution center. In order to verify the effectiveness of order clustering analysis and COI storage analysis for seeding sorting, the storage locations were randomly arranged and the COI descending order was arranged on the two-way rotating shelves. Two groups of orders close to the central cluster were selected and simulated by seeding time model. Calculate the final picking time. The model can verify the validity and feasibility of the order clustering analysis method in the storage optimization, and provide theoretical and practical guidance in the planning of distribution center.
【学位授予单位】：昆明理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F252;F426.72
【参考文献】
相关期刊论文 前10条
1 卢烨彬;刘少轩;;随机存储机制下基于引力模型的订单波次划分方法的研究[J];管理现代化;2016年04期
2 王旭坪;张s，
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