本文選題：云制造 + 制造資源��； 參考：《哈爾濱理工大學(xué)》2015年博士論文

【摘要】：云制造是一種面向服務(wù)的網(wǎng)絡(luò)化制造新模式,它為中國(guó)制造業(yè)的服務(wù)化轉(zhuǎn)型提供一種新的思路,但其還沒(méi)有達(dá)到真正的落地實(shí)現(xiàn)的程度。作為網(wǎng)絡(luò)化制造的一種模式,云制造強(qiáng)調(diào)按需獲取資源,這一點(diǎn)正好符合互聯(lián)網(wǎng)時(shí)代的制造企業(yè)對(duì)資源全面共享的訴求。邏輯資源的抽取和服務(wù)化是云制造的基礎(chǔ),本文以云制造環(huán)境下制造過(guò)程中加工制造階段作為研究對(duì)象,搭建加工制造資源虛擬化框架,為了解決架構(gòu)中資源如何描述、虛擬資源如何抽取和資源發(fā)現(xiàn)與優(yōu)選的問(wèn)題,從加工制造資源建模方法、加工制造資源的映射方法、制造資源選擇與優(yōu)化方法三個(gè)方面進(jìn)行了深入研究。根據(jù)加工制造資源的特點(diǎn),構(gòu)建底層的資源虛擬化架構(gòu),建立虛擬資源抽取模型。建立基于元模型的加工制造資源及其虛擬資源的兩層模型結(jié)構(gòu),研究加工制造資源的邏輯資源抽取策略。在分析本體概念的基礎(chǔ)上,結(jié)合加工制造資源的特點(diǎn),提出加工制造資源及其虛擬資源的元概念和元屬性的形式化定義。在元模型的語(yǔ)義和語(yǔ)法的約束下,采用本體建模工具protégé和語(yǔ)義Web本體描述語(yǔ)言O(shè)WL,建立加工制造資源及其虛擬資源的模型層,通過(guò)切削加工資源虛擬化原型系統(tǒng)進(jìn)行驗(yàn)證。在此基礎(chǔ)上,提出資源組合模型和組合服務(wù)模型。依據(jù)加工制造資源的特性,建立其虛擬化映射模型,分析映射的基本規(guī)則和實(shí)現(xiàn)流程。研究了基于ai Net人工免疫網(wǎng)絡(luò)的資源聚類方法;為解決ai Net網(wǎng)絡(luò)呈現(xiàn)無(wú)規(guī)律的動(dòng)態(tài)變化的問(wèn)題,定義優(yōu)化目標(biāo)函數(shù),提出改進(jìn)的ai Net免疫學(xué)習(xí)算法。對(duì)算法的時(shí)間復(fù)雜度和合理性進(jìn)行了評(píng)價(jià),并對(duì)其進(jìn)行了實(shí)例驗(yàn)證。研究加工制造資源—虛擬資源的語(yǔ)義本體映射方法,分析了基于語(yǔ)義相等的映射實(shí)現(xiàn)原理。依據(jù)加工制造任務(wù)的對(duì)象特性和云制造的特點(diǎn),在資源云池的基礎(chǔ)上,研究加工制造過(guò)程中資源發(fā)現(xiàn)的流程,建立加工制造任務(wù)的形式化模型,闡述了任務(wù)分解的原則。為保證子任務(wù)集獲得最優(yōu)的資源集,研究資源候選集的優(yōu)化選擇方法,建立加工制造資源優(yōu)選的評(píng)價(jià)指標(biāo)體系。利用模糊層次分析法的模糊一致比較矩陣對(duì)評(píng)價(jià)指標(biāo)的權(quán)重進(jìn)行評(píng)價(jià),給出權(quán)重評(píng)價(jià)向量。在云制造環(huán)境下,加工制造任務(wù)鏈?zhǔn)谴⑿泄泊妗⒓庸ぶ圃熨Y源異地共享,為此,時(shí)間和成本兩個(gè)評(píng)價(jià)因素中引入物流和倉(cāng)儲(chǔ)的時(shí)間和成本。依據(jù)評(píng)價(jià)指標(biāo)體系,建立資源優(yōu)選多目標(biāo)函數(shù);依據(jù)遺傳算法全局搜索性與精英保留策略,實(shí)現(xiàn)資源優(yōu)選算法的設(shè)計(jì),給出了相應(yīng)的算法流程。最后通過(guò)切削加工類資源的虛擬化原型系統(tǒng)和軸承座組件加工實(shí)例對(duì)上述理論進(jìn)行了驗(yàn)證。
[Abstract]:Cloud manufacturing is a new service-oriented networked manufacturing model, which provides a new way of thinking for the service transformation of Chinese manufacturing industry, but it has not reached the real level of realization. As a model of networked manufacturing, cloud manufacturing emphasizes on acquiring resources on demand, which is exactly in line with the demand for comprehensive sharing of resources in the manufacturing enterprises in the Internet era. Logical resource extraction and service are the basis of cloud manufacturing. This paper takes the manufacturing phase of manufacturing process in the cloud manufacturing environment as the research object, builds the virtual framework of manufacturing resources, in order to solve the problem of how to describe the resources in the architecture. The problems of how to extract virtual resources and how to find and select resources are studied in this paper from three aspects: modeling method of manufacturing resources mapping method of manufacturing resources selection and optimization of manufacturing resources. According to the characteristics of manufacturing resources, a virtual resource extraction model is established. A two-layer model structure of machining manufacturing resources and its virtual resources based on metamodel is established, and the logical resource extraction strategy of processing manufacturing resources is studied. Based on the analysis of ontology concept and the characteristics of machining manufacturing resources, the formal definition of meta-concept and meta-attribute of machining manufacturing resources and their virtual resources is proposed. Under the constraints of semantics and syntax of metamodel, the model layer of machining manufacturing resources and virtual resources is established by using ontology modeling tool prot 茅 g 茅 and semantic Web ontology description language owl, and verified by cutting machining resource virtualization prototype system. On this basis, a resource composition model and a composite service model are proposed. According to the characteristics of manufacturing resources, the virtual mapping model is established, and the basic rules and implementation flow of mapping are analyzed. The resource clustering method based on ai Net artificial immune network is studied. In order to solve the problem that ai Net network presents irregular dynamic change, the optimization objective function is defined, and an improved ai Net immune learning algorithm is proposed The time complexity and rationality of the algorithm are evaluated and verified by an example. The semantic ontology mapping method of processing manufacturing resources-virtual resources is studied, and the principle of mapping based on semantic equality is analyzed. According to the object characteristics of manufacturing tasks and the characteristics of cloud manufacturing, based on the resource cloud pool, the process of resource discovery in manufacturing process is studied, the formalized model of manufacturing tasks is established, and the principle of task decomposition is expounded. In order to ensure the subtask set to obtain the optimal resource set, the optimal selection method of the resource candidate set is studied, and the evaluation index system of the processing manufacturing resource optimal selection is established. The weight of the evaluation index is evaluated by the fuzzy uniform comparison matrix of the fuzzy analytic hierarchy process, and the weight evaluation vector is given. In the cloud manufacturing environment, the processing manufacturing task chain coexists in parallel, and the processing manufacturing resources are shared in different places. Therefore, the time and cost of logistics and storage are introduced into the evaluation factors of time and cost. According to the evaluation index system, the multi-objective function of the optimal selection of resources is established, and the design of the optimal selection algorithm of resources is realized according to the global search ability of genetic algorithm and the strategy of elite reservation, and the corresponding algorithm flow is given. Finally, the above theory is verified by the virtual prototype system of machining resources and the example of housing component machining.
【學(xué)位授予單位】：哈爾濱理工大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2015
【分類號(hào)】：TH164

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