本文選題：維修備件　切入點(diǎn)：需求預(yù)測(cè)　出處：《北京交通大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：隨著社會(huì)向"互聯(lián)網(wǎng)+"方向發(fā)展,高校信息化已經(jīng)成為新形勢(shì)下高等學(xué)校建設(shè)的基礎(chǔ)工作,而高校后勤信息化則是其重要組成部分。在"互聯(lián)網(wǎng)+高校后勤"的背景下,將以互聯(lián)網(wǎng)為主的現(xiàn)代化信息技術(shù)引入后勤管理已成為必然趨勢(shì),其目的在于實(shí)現(xiàn)管理的數(shù)字化、網(wǎng)絡(luò)化和智能化。為師生提供便捷的維修服務(wù)是高校后勤的核心工作之一,因此維修備件的采購管理成為該項(xiàng)工作的重點(diǎn)。隨著高校的逐年擴(kuò)招,維修備件的種類和數(shù)量大幅增加,給管理帶來了新的挑戰(zhàn)。目前,高校后勤維修備件的采購管理存在著"缺乏控制重點(diǎn)、缺乏需求預(yù)測(cè)機(jī)制、缺乏有效的采購策略"等諸多問題,并且管理方式較為落后,大多以傳統(tǒng)的人工方式為主,雖然部分高校引入了采購管理軟件,但功能僅僅是簡(jiǎn)單的記賬和統(tǒng)計(jì),無法為管理者提供決策支持。針對(duì)以上問題,本文主要進(jìn)行了兩方面的研究工作:①根據(jù)高校后勤維修備件特點(diǎn),對(duì)采購管理方法進(jìn)行改進(jìn):提出了維修備件分類、需求預(yù)測(cè)、采購策略等模型與算法;②以A高校后勤維修中心為例,在所提模型的基礎(chǔ)上,設(shè)計(jì)并開發(fā)了具有優(yōu)化采購決策功能的維修備件采購管理系統(tǒng)。具體內(nèi)容如下:(1)采用基于DEA(數(shù)據(jù)包絡(luò)分析)的ABC分類方法對(duì)維修備件按重要程度進(jìn)行分類,從而明確庫存控制的重點(diǎn),為采購管理工作奠定基礎(chǔ)。(2)針對(duì)重要程度較高的A類維修備件提出需求預(yù)測(cè)方法,包括連續(xù)型需求預(yù)測(cè)和間斷型需求預(yù)測(cè)兩種。在連續(xù)型需求預(yù)測(cè)方法中,采用"簡(jiǎn)單季節(jié)性指數(shù)平滑模型"、"Holt-Winters相乘性模型"和"自回歸移動(dòng)平均模型(ARIMA)"三種模型分別進(jìn)行預(yù)測(cè),最后通過預(yù)測(cè)精度的對(duì)比,選出Holt-Winters相乘性模型為最佳預(yù)測(cè)模型;在間斷型需求預(yù)測(cè)方法中,本文采用了 Croston方法,并進(jìn)行了實(shí)例分析。(3)提出高校后勤維修備件的采購策略。對(duì)于A類備件,采用單品種動(dòng)態(tài)批量采購模型(Wagner-Whitin算法)和多品種動(dòng)態(tài)批量采購模型。對(duì)于B、C類備件,采用考慮安全庫存的(t,s,Q)采購庫存模型。(4)以A高校后勤維修中心為例,設(shè)計(jì)和開發(fā)了高校后勤維修備件采購管理系統(tǒng),并將備件分類、需求預(yù)測(cè)、采購庫存策略等決策模型運(yùn)用到系統(tǒng)中,能夠科學(xué)地預(yù)測(cè)最優(yōu)采購批量及采購時(shí)間,從而實(shí)現(xiàn)了該系統(tǒng)的輔助決策功能。
[Abstract]:With the development of society towards the "Internet", the informationization of colleges and universities has become the basic work of the construction of colleges and universities under the new situation, and the informationization of university logistics is an important part of it. It has become an inevitable trend to introduce modern information technology based on the Internet into logistics management. Its purpose is to realize the digitalization, networking and intelligentization of management, and to provide convenient maintenance services for teachers and students is one of the core tasks of logistics in colleges and universities. Therefore, the purchasing management of maintenance spare parts has become the focus of this work. With the increasing enrollment of colleges and universities year by year, the types and quantity of maintenance spare parts have increased dramatically, which has brought new challenges to the management. There are many problems in the procurement management of spare parts for logistics maintenance in colleges and universities, such as "lack of control focus, lack of demand forecasting mechanism, lack of effective purchasing strategy", and the management mode is relatively backward, most of which are dominated by traditional manual methods. Although some colleges and universities have introduced procurement management software, but the function is only simple accounting and statistics, can not provide decision support for managers. This paper mainly carried out two aspects of research work: 1. According to the characteristics of spare parts for logistics maintenance in colleges and universities, the purchasing management method was improved: the classification of maintenance spare parts, the forecast of demand, Procurement strategy model and algorithm 2 A university logistics maintenance center as an example, on the basis of the proposed model, This paper designs and develops a maintenance spare parts purchasing management system with the function of optimizing purchasing decision. The main contents are as follows: (1) ABC classification method based on DEA-based data Envelopment Analysis (DEA) is used to classify maintenance spare parts according to their importance. Therefore, the emphasis of inventory control is clarified, and the basis for purchasing management is laid. (2) the forecasting method of demand for class A maintenance spare parts, which is of high importance, is put forward. There are two kinds of continuous demand forecasting and discontinuous demand forecasting. In the continuous demand forecasting method, three kinds of models, namely "simple seasonal exponential smoothing model", "Holt-Winters multiplicative model" and "autoregressive moving average model (ARIMA)", are used to forecast the demand. Finally, the Holt-Winters multiplicative model is selected as the best prediction model by comparing the prediction accuracy. In the discontinuous demand forecasting method, the Croston method is used in this paper. A case study is carried out. (3) the purchasing strategy of spare parts for logistic maintenance in colleges and universities is put forward. For class A spare parts, Wagner-Whitin algorithm and multi-variety dynamic batch purchasing model are used for class A spare parts. This paper introduces the purchasing inventory model of QM) which considers safety inventory. Taking A university logistics maintenance center as an example, the paper designs and develops the purchasing management system of spare parts for university logistics maintenance, and classifies the spare parts and forecasts the demand. The decision model such as purchasing inventory strategy is applied to the system, which can scientifically predict the optimal purchase batch and purchase time, thus realizing the auxiliary decision function of the system.
【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：G647.4

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本文編號(hào)：1597883