【摘要】：隨著“工業(yè)4.0”時代的到來,信息技術(shù)與工業(yè)制造技術(shù)高度融合、深度交織產(chǎn)生了新的制造模式——云制造。該模式利用云制造服務(wù)平臺,按用戶的實際需求組織平臺中的制造資源,給用戶提供各類制造服務(wù),為解決當(dāng)前我國制造領(lǐng)域存在的不合理利用制造資源而引起資源浪費(fèi)的問題提供了新的解決思路。因此,如何從云制造平臺大量的共享制造資源中選擇合適的制造服務(wù)成了研究熱點。本文以汽車制造廠零部件生產(chǎn)為例,研究了相應(yīng)的制造商選擇問題,通過制造云服務(wù)選擇方法為汽車制造廠選擇最合適的零部件生產(chǎn)制造云服務(wù)商,從而使得汽車制造廠最大限度滿足自身的制造需求。本文的研究亦可為其他制造企業(yè)在制造云服務(wù)選擇問題上提供參考。首先,本文通過查閱大量相關(guān)文獻(xiàn)資料,結(jié)合制造資源和網(wǎng)絡(luò)性能兩方面,構(gòu)建了一套具有制造云服務(wù)特色的QoS(Quality of Service)評價指標(biāo)體系。然后,針對制造云服務(wù)隨時間變化的特性,引入“時間序列”的概念,將制造云服務(wù)QoS動態(tài)變化情況用時間序列形式表達(dá)。考慮到實際應(yīng)用中由于設(shè)備故障等原因情況,會出現(xiàn)QoS觀測數(shù)據(jù)在某些時間序列節(jié)點缺失的問題。本文利用基于云服務(wù)QoS序列特性的缺失值估計方法預(yù)測和填補(bǔ)相應(yīng)的缺失值,較好地解決了這一問題。其次,本文提出了一種基于主客觀綜合權(quán)重的云服務(wù)時間序列選擇方法。從基于用戶QoS偏好層次的主觀權(quán)重和基于QoS指標(biāo)相關(guān)性的客觀權(quán)重兩個角度進(jìn)行考慮,通過結(jié)合時間序列QoS模型進(jìn)行云服務(wù)選擇,為制造企業(yè)提供幫助。最后,通過仿真實驗分析表明,該方法在有效解決用戶QoS偏好的同時又充分考慮云服務(wù)集的QoS指標(biāo)的數(shù)據(jù)分布特性,選擇結(jié)果具有較高的準(zhǔn)確性與科學(xué)性。
[Abstract]:With the arrival of the "industry 4.0" era, information technology and industrial manufacturing technology are highly integrated, and a new manufacturing model-cloud manufacturing is produced by the deep interweaving of information technology and industrial manufacturing technology. This model uses the cloud manufacturing service platform to organize the manufacturing resources in the platform according to the actual needs of the users, and provides all kinds of manufacturing services to the users. It provides a new way to solve the problem of resource waste caused by irrational use of manufacturing resources in the field of manufacturing in China. Therefore, how to select suitable manufacturing services from a large number of shared manufacturing resources on cloud manufacturing platform has become a hot research topic. In this paper, taking the manufacture of parts and components in automobile factory as an example, the problem of manufacturer selection is studied. Through the method of manufacturing cloud service selection, the most suitable component manufacturing cloud service provider is selected for automobile manufacturing plant. In order to make the automobile factory to meet its own manufacturing needs to the maximum extent. The research in this paper can also provide reference for other manufacturing enterprises in the selection of manufacturing cloud services. Firstly, this paper constructs a set of QoS (Quality of Service) evaluation index system with the characteristics of manufacturing cloud service by consulting a lot of relevant literature and combining manufacturing resources and network performance. Then, according to the characteristics of manufacturing cloud service with time, the concept of "time series" is introduced, and the dynamic change of manufacturing cloud service QoS is expressed in the form of time series. Considering the situation of equipment failure and other reasons in practical application, the problem of missing QoS observation data in some time series nodes will occur. In this paper, the method of estimating the missing values based on the characteristics of cloud service QoS sequences is used to predict and fill the corresponding missing values, which solves this problem well. Secondly, this paper proposes a cloud service time series selection method based on subjective and objective weight synthesis. Considering the subjective weight based on the user QoS preference level and the objective weight based on the correlation of QoS index, the cloud service selection is carried out by combining the time series QoS model to provide help for manufacturing enterprises. Finally, the simulation results show that the method not only solves the user's QoS preference effectively, but also fully considers the data distribution characteristics of the QoS index of the cloud service set, and the selection result is accurate and scientific.
【學(xué)位授予單位】：南京航空航天大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：F424;F49

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本文編號：2232417