本文選題：物聯(lián)網(wǎng)　切入點：決策支持系統(tǒng)　出處：《燕山大學》2014年碩士論文

【摘要】：工業(yè)化與信息化融合的背景下，我國工業(yè)企業(yè)在發(fā)展壯大過程中開始更多地借助科技力量。粗放型的經(jīng)濟發(fā)展模式以及傳統(tǒng)的工業(yè)生產(chǎn)工藝對人力資源、自然能源都造成了很大的浪費，對此現(xiàn)狀，本文提出了以工業(yè)企業(yè)為背景的物聯(lián)網(wǎng)與決策支持融合系統(tǒng)的設計方案，將物聯(lián)網(wǎng)技術應用到工業(yè)企業(yè)中，并結合企業(yè)決策支持系統(tǒng)進行融合架構，實現(xiàn)工業(yè)生產(chǎn)管理過程的全面感知和智能決策。 本文在概述了融合系統(tǒng)的研究背景、課題意義和相關理論基礎上，，面向工業(yè)企業(yè)的實際需求，以構建物聯(lián)網(wǎng)與決策支持融合系統(tǒng)為目標，圍繞融合系統(tǒng)整體架構和層次設計問題展開研究。首先，對融合系統(tǒng)進行整體構建，建立底層感知層和上層決策層緊密銜接的信息化系統(tǒng)，感知層具備全面感知監(jiān)測功能，決策層為企業(yè)的生產(chǎn)活動提供決策支持；其次，選擇復雜網(wǎng)絡理論作為研究切入點，利用小世界網(wǎng)絡模型對融合系統(tǒng)感知層進行網(wǎng)絡拓撲結構優(yōu)化，以及應用網(wǎng)絡化數(shù)據(jù)挖掘算法實現(xiàn)對決策數(shù)據(jù)的挖掘處理，發(fā)現(xiàn)其中蘊含的結構性知識和動態(tài)變化規(guī)律；最后，將本系統(tǒng)的研究應用于實際企業(yè)生產(chǎn)過程，獲取某輪轂生產(chǎn)企業(yè)的鑄造工藝過程實時數(shù)據(jù)，對影響成品質量的因素進行分析，運用決策支持子系統(tǒng)的數(shù)據(jù)挖掘方法獲得可視化決策知識，以實現(xiàn)企業(yè)實時智能化管理。
[Abstract]:Under the background of the integration of industrialization and information technology, Chinese industrial enterprises begin to rely more on scientific and technological power, extensive economic development model and traditional industrial production technology to human resources in the process of development and expansion. The natural energy has caused a great waste. In view of the present situation, this paper puts forward the design scheme of the integration system of Internet of things and decision support based on the industrial enterprises, and applies the technology of the Internet of things to the industrial enterprises. Combined with the enterprise decision support system (DSS), it can realize the overall perception and intelligent decision of the industrial production management process. Based on an overview of the research background, significance and related theories of fusion system, this paper aims at building a fusion system of Internet of things and decision support, which is oriented to the actual needs of industrial enterprises. First of all, we construct the fusion system as a whole, and establish the information system which is closely connected between the bottom perception layer and the upper decision-making layer. The perception layer has the function of overall perception and monitoring. Decision layer provides decision support for enterprise production activities. Secondly, the complex network theory is selected as the starting point to optimize the network topology structure of the fusion system perception layer by using the small-world network model. And using the network data mining algorithm to realize the mining of decision data, and find the structural knowledge and dynamic change law. Finally, the research of this system is applied to the actual enterprise production process. The real-time data of casting process in a hub manufacturing enterprise are obtained, the factors affecting the quality of finished product are analyzed, and the visual decision knowledge is obtained by using the data mining method of decision support subsystem, so as to realize the real-time intelligent management of the enterprise.
【學位授予單位】：燕山大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TP311.13;TP391.44;TN929.5

【參考文獻】

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本文編號：1662647