播種式揀選技術(shù)在某大型醫(yī)藥配送中心的應(yīng)用研究
發(fā)布時間：2018-08-07 11:14
【摘要】：在醫(yī)療衛(wèi)生事業(yè)蓬勃發(fā)展的今天,國民對醫(yī)療健康的關(guān)注度整體提高,國家對醫(yī)療事業(yè)建設(shè)的投入也隨之加大,加之,現(xiàn)代醫(yī)療自身水平的發(fā)展,醫(yī)藥行業(yè)朝著更加多樣化與個性化的方向發(fā)展,這就要求醫(yī)藥企業(yè)通過對自身的完善來提高整個醫(yī)療市場的服務(wù)水平,同時醫(yī)藥的配送速度關(guān)系到病人的生命安危,所以要求醫(yī)藥配送中心能夠更快的對訂單做出反應(yīng),為顧客提供更及時的配送,因為醫(yī)藥的種類繁多,客戶的個性化選擇更多,訂單也朝著中小批量轉(zhuǎn)換,配送中心對分揀時效性的要求也越來越高,因此,本文通過對某醫(yī)藥配送中心的研究,將客戶訂單作為基本的研究方向。根據(jù)訂單的特點匹配最優(yōu)的揀選方式。本文首先對當(dāng)前國內(nèi)外醫(yī)藥配送中心的研究及發(fā)展?fàn)顩r進(jìn)行簡單介紹,同時對配送中心的揀選策略及訂單的處理方式進(jìn)行描述,對醫(yī)藥配送中心在整個醫(yī)藥供應(yīng)鏈上得作用進(jìn)行了介紹,然后對醫(yī)藥的揀選作業(yè)方式進(jìn)行了區(qū)分,并將EIQ的分析引入到訂單分析當(dāng)中,將其分解為EQ、EN、IQ、IK四種分析方法。為了彌補(bǔ)在訂單的品項構(gòu)成和分布情況上的不足,本文又引入訂單矩陣對訂單及品項特點進(jìn)行研究。將訂單的行向量作為訂單量,列向量作為品項,同時相應(yīng)的加入了訂單的訂貨頻次及訂單的單品數(shù)量。然后本文又在訂單矩陣的基礎(chǔ)上提出了聚類算法,使用帕累托曲線對訂單及品項進(jìn)行篩選,利用K-平均聚類對原有的訂單矩陣進(jìn)行品項及訂單分析,然后生成最終的分類訂單矩陣。將不同類型的訂單及品項根據(jù)聚集簇進(jìn)行劃分,以此來明確配送中心的訂單分析策略。為驗證訂單在聚類分析以及COI儲位分析對于播種式揀選方式具有有效優(yōu)化效果,將儲位進(jìn)行隨機(jī)排列以及COI降序排列兩種方式在雙向旋轉(zhuǎn)貨架上進(jìn)行貨品的擺放。選取靠近中心簇的兩組訂單,通過播種式揀選的時間模型對兩種排列方式進(jìn)行仿真分析。對最終的揀選時間進(jìn)行計算。該模型能夠驗證訂單的聚類分析方法在儲位優(yōu)化上的有效性及可行性,在配送中心的規(guī)劃上提供理論及現(xiàn)實的指導(dǎo)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.
【學(xué)位授予單位】：昆明理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：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.
【學(xué)位授予單位】：昆明理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：F252;F426.72
【參考文獻(xiàn)】
相關(guān)期刊論文 前10條
1 盧燁彬;劉少軒;;隨機(jī)存儲機(jī)制下基于引力模型的訂單波次劃分方法的研究[J];管理現(xiàn)代化;2016年04期
2 王旭坪;張s，
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