基于客戶需求的紡機行業(yè)訂單預測研究
發(fā)布時間：2018-07-26 15:25
【摘要】：隨著市場和科學技術(shù)的快速發(fā)展，消費者需求呈現(xiàn)出多樣化和細分化的趨勢，制造企業(yè)逐步轉(zhuǎn)化為多品種小批量的生產(chǎn)方式。紡機企業(yè)面臨著在滿足客戶多樣化需求的前提下，降低生產(chǎn)成本，減少浪費，提高紡機產(chǎn)品質(zhì)量的巨大挑戰(zhàn)，訂單作為客戶需求的體現(xiàn)和企業(yè)的生命，研究在復雜多變的市場環(huán)境下對做出準確的訂單預測可以有效的解決上述問題。 隨著信息化技術(shù)的發(fā)展，紡織機械制造企業(yè)通過采用信息管理系統(tǒng)，在數(shù)據(jù)庫中存儲了大量的銷售訂單歷史數(shù)據(jù)，本文依據(jù)企業(yè)的銷售數(shù)據(jù)，分析客戶需求的變化特征和影響因素，以此作為歷史訂單數(shù)據(jù)的研究切點，從而建立訂單預測模型。本文主要工作如下： （1）介紹了制造行業(yè)的背景和產(chǎn)品特點，在此基礎上詳細介紹了訂單預測的相關知識和研究現(xiàn)狀，，指出了常見訂單預測方法的不足，提出了面向客戶需求建立紡機企業(yè)的訂單預測模型。 （2）闡述了客戶需求與訂單的辯證關系，在紡機行業(yè)的歷史銷售數(shù)據(jù)規(guī)范完整的基礎上，分析了客戶需求對于訂單預測的重要意義，提出了從傳統(tǒng)時間序列預測方法轉(zhuǎn)為針對客戶需求的訂單預測方法。 （3）依據(jù)實時銷售數(shù)據(jù)，并結(jié)合紡機市場分析客戶需求的變動特征，提出相關的客戶需求模糊影響因子，構(gòu)建一種新的基于客戶需求模糊影響因子的時間序列分解訂單預測方法，并對本文所采用的模型建立方法和預測原理進行了相關的闡述。與此同時提出結(jié)合實際終端客戶訂單情況進行對比分析，在對比分析的基礎上，對訂單預測方法作出評價。 （4）結(jié)合具體紡機企業(yè)，對訂單預測模型進行軟件開發(fā)與驗證。對紡機企業(yè)的訂單管理與預測系統(tǒng)進行了需求和目標分析，研究系統(tǒng)的框架和開發(fā)環(huán)境，并依據(jù)模型原理進行功能結(jié)構(gòu)設計，最后在案例中對紡機企業(yè)的訂單管理與預測系統(tǒng)進行實例應用，為后續(xù)生產(chǎn)活動的開展提供有效可靠的訂單信息。 最后對全文的研究內(nèi)容進行總結(jié)，分析其存在的不足，并對課題的后續(xù)研究進行展望。
[Abstract]:With the rapid development of market and science and technology, the consumer demand shows a trend of diversification and differentiation. Spinning machine enterprises are faced with the huge challenge of reducing production cost, reducing waste and improving the quality of spinning machine products under the premise of meeting the diversified needs of customers. Order is the embodiment of customer demand and the life of enterprises. The research can solve the above problems effectively by making accurate order forecasting in the complex and changeable market environment. With the development of information technology, textile machinery manufacturing enterprises store a large number of historical data of sales orders in the database by adopting information management system. The changing characteristics and influencing factors of customer demand are analyzed, which is used as the research point of historical order data, and then the order prediction model is established. The main work of this paper is as follows: (1) the background and product characteristics of manufacturing industry are introduced. On this basis, the related knowledge and research status of order forecasting are introduced in detail, and the shortcomings of common order forecasting methods are pointed out. In this paper, the order forecasting model of spinning machine enterprises is proposed to meet customer demand. (2) the dialectical relationship between customer demand and order is expounded. On the basis of the standardization and integrity of historical sales data of spinning machine industry, This paper analyzes the importance of customer demand to order forecasting, and puts forward an order forecasting method from traditional time series forecasting method to customer demand forecasting method. (3) according to the real time sales data, Based on the analysis of changing characteristics of customer demand in spinning machine market, a new forecasting method of time series decomposing order based on fuzzy influence factor of customer demand is proposed. The modeling method and prediction principle used in this paper are also expounded. At the same time, the paper puts forward a comparative analysis of the actual end-customer order, and evaluates the forecasting method of the order on the basis of the comparative analysis. (4) combined with the specific spinning machine enterprise, The order prediction model is developed and validated. The requirements and objectives of the order management and prediction system of spinning machine enterprises are analyzed, the framework and development environment of the system are studied, and the functional structure is designed according to the principle of the model. Finally, an example is given to the order management and prediction system of spinning machine enterprises, which provides effective and reliable order information for the subsequent production activities. Finally, the paper summarizes the research content, analyzes its shortcomings, and looks forward to the future research.
【學位授予單位】：武漢理工大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：F224;F426.81
本文編號：2146447
[Abstract]:With the rapid development of market and science and technology, the consumer demand shows a trend of diversification and differentiation. Spinning machine enterprises are faced with the huge challenge of reducing production cost, reducing waste and improving the quality of spinning machine products under the premise of meeting the diversified needs of customers. Order is the embodiment of customer demand and the life of enterprises. The research can solve the above problems effectively by making accurate order forecasting in the complex and changeable market environment. With the development of information technology, textile machinery manufacturing enterprises store a large number of historical data of sales orders in the database by adopting information management system. The changing characteristics and influencing factors of customer demand are analyzed, which is used as the research point of historical order data, and then the order prediction model is established. The main work of this paper is as follows: (1) the background and product characteristics of manufacturing industry are introduced. On this basis, the related knowledge and research status of order forecasting are introduced in detail, and the shortcomings of common order forecasting methods are pointed out. In this paper, the order forecasting model of spinning machine enterprises is proposed to meet customer demand. (2) the dialectical relationship between customer demand and order is expounded. On the basis of the standardization and integrity of historical sales data of spinning machine industry, This paper analyzes the importance of customer demand to order forecasting, and puts forward an order forecasting method from traditional time series forecasting method to customer demand forecasting method. (3) according to the real time sales data, Based on the analysis of changing characteristics of customer demand in spinning machine market, a new forecasting method of time series decomposing order based on fuzzy influence factor of customer demand is proposed. The modeling method and prediction principle used in this paper are also expounded. At the same time, the paper puts forward a comparative analysis of the actual end-customer order, and evaluates the forecasting method of the order on the basis of the comparative analysis. (4) combined with the specific spinning machine enterprise, The order prediction model is developed and validated. The requirements and objectives of the order management and prediction system of spinning machine enterprises are analyzed, the framework and development environment of the system are studied, and the functional structure is designed according to the principle of the model. Finally, an example is given to the order management and prediction system of spinning machine enterprises, which provides effective and reliable order information for the subsequent production activities. Finally, the paper summarizes the research content, analyzes its shortcomings, and looks forward to the future research.
【學位授予單位】：武漢理工大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：F224;F426.81
【參考文獻】
相關期刊論文 前10條
1 熊高峰;韓鵬;聶坤凱;;時間序列分解在短期電價分析與預測中的應用[J];電力系統(tǒng)及其自動化學報;2011年03期
2 李江,萬映紅,李懷祖;客戶關系管理中客戶需求知識建模研究[J];管理工程學報;2004年04期
3 姚智勝;邵春福;熊志華;;支持向量機在路段行程時間預測中的應用研究[J];公路交通科技;2007年09期
4 宮蓉蓉;;基于OLS與EPSO算法的RBF企業(yè)訂單預測模型研究[J];計算機工程與應用;2011年22期
5 但斌;王江平;劉瑜;;大規(guī)模定制環(huán)境下客戶需求信息分類模型及其表達方法研究[J];計算機集成制造系統(tǒng);2008年08期
6 劉樝;戴敏;張志勝;史金飛;;基于滑動平均訂單預測的半導體生產(chǎn)庫存模型[J];計算機集成制造系統(tǒng);2010年02期
7 葛彥強;汪向征;王愛民;;改進灰色神經(jīng)網(wǎng)絡的冰箱訂單需求預測研究[J];計算機仿真;2012年05期
8 董曉慧;李春琳;邱亞蘭;;機械產(chǎn)品銷售預測GP算法研究與系統(tǒng)實現(xiàn)[J];制造業(yè)自動化;2010年01期
9 霍國慶;企業(yè)戰(zhàn)略信息管理的理論模型[J];南開管理評論;2002年01期
10 戴寶印;;基于層次分析法及BP神經(jīng)網(wǎng)絡的我國船舶訂單預測研究[J];物流科技;2010年02期
本文編號：2146447
本文鏈接：http://sikaile.net/jingjilunwen/jingjiguanlilunwen/2146447.html
最近更新
教材專著
