本文關(guān)鍵詞：云制造模式下建材裝備企業(yè)制造任務(wù)執(zhí)行關(guān)鍵技術(shù)研究　出處：《武漢理工大學(xué)》2013年博士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 云制造 語義建模 演化博弈論 執(zhí)行服務(wù)鏈 過程監(jiān)控

【摘要】：隨著云計(jì)算、物聯(lián)網(wǎng)等先進(jìn)技術(shù)的迅猛發(fā)展和制造業(yè)所面臨的挑戰(zhàn),云制造模式和技術(shù)應(yīng)運(yùn)而生,其核心在于實(shí)現(xiàn)制造資源的協(xié)同和共享,為制造業(yè)的升級(jí)轉(zhuǎn)型提供了新的推動(dòng)力。然而,由于云制造模式的開放性及多用戶等特征,導(dǎo)致多用戶任務(wù)執(zhí)行過程涉及到制造任務(wù)的異構(gòu)性、任務(wù)資源服務(wù)的競(jìng)爭(zhēng)性、狀態(tài)監(jiān)控和任務(wù)執(zhí)行后的評(píng)價(jià)等問題。對(duì)此,本文從四個(gè)方面來研究云制造模式下制造任務(wù)的優(yōu)化執(zhí)行,并以建材裝備企業(yè)為應(yīng)用對(duì)象進(jìn)行實(shí)踐研究。主要研究工作可以概括為以下幾個(gè)方面： (1)針對(duì)制造任務(wù)執(zhí)行過程中的任務(wù)異構(gòu)性問題,提出了云制造任務(wù)的信息模型和語義建�？蚣�,首先應(yīng)用本體建模技術(shù)建立了初始云制造任務(wù)本體(OCMT_Ontology),以建材裝備企業(yè)制造任務(wù)文本庫為基礎(chǔ)結(jié)合文本處理技術(shù),通過本體自學(xué)習(xí)模型建立并完善通用云制造任務(wù)本體(GCMT_Ontology);在此基礎(chǔ)基礎(chǔ)之上,通過匹配GCMT_Ontology,構(gòu)建云制造任務(wù)子本體(CMTS_ontology)來實(shí)現(xiàn)云制造任務(wù)的語義描述。 (2)提出了云制造任務(wù)執(zhí)行服務(wù)鏈構(gòu)建框架,在分析單用戶資源服務(wù)優(yōu)選的基礎(chǔ)上,重點(diǎn)研究多用戶任務(wù)資源服務(wù)優(yōu)選模型,針對(duì)多用戶對(duì)資源服務(wù)的競(jìng)爭(zhēng),提出了應(yīng)用演化博弈論的方法構(gòu)建多用戶資源服務(wù)的博弈模型,按照任務(wù)執(zhí)行是否延期分四種類型求解博弈模型的演化穩(wěn)定策略,并分析其動(dòng)態(tài)復(fù)制方程的演化相圖。最后,依據(jù)制造子任務(wù)的時(shí)序邏輯關(guān)系來構(gòu)建可執(zhí)行的協(xié)同制造資源服務(wù)鏈。 (3)提出云制造模式下任務(wù)執(zhí)行過程狀態(tài)監(jiān)控框架,構(gòu)建了基于制造任務(wù)子本體的多源數(shù)據(jù)一致映射模型,按照制造任務(wù)的結(jié)構(gòu)和執(zhí)行服務(wù)鏈實(shí)現(xiàn)任務(wù)執(zhí)行進(jìn)度的數(shù)據(jù)融合,根據(jù)制造資源實(shí)時(shí)監(jiān)控的數(shù)據(jù),應(yīng)用隱性馬爾科夫模型實(shí)現(xiàn)制造資源狀態(tài)的實(shí)時(shí)監(jiān)控。 (4)提出了云制造任務(wù)執(zhí)行過程評(píng)估模型,并建立了不同執(zhí)行階段的評(píng)估指標(biāo)及模糊化處理方法。提出直覺模糊OWA-TOPSIS的方法對(duì)任務(wù)執(zhí)行過程進(jìn)行評(píng)估,構(gòu)架了六類不同的TOPSIS數(shù)據(jù)累積方法和最佳和最差理想點(diǎn)的識(shí)別方法,并通過案例研究驗(yàn)證了提出方法的實(shí)用性。 (5)從實(shí)際應(yīng)用出發(fā),針對(duì)建材裝備制造企業(yè)產(chǎn)品的制造過程,開發(fā)了云制造模式下任務(wù)執(zhí)行過程管理系統(tǒng),并在協(xié)同制造的多個(gè)企業(yè)間實(shí)現(xiàn)任務(wù)執(zhí)行計(jì)劃管理、過程跟蹤和評(píng)價(jià)。
[Abstract]:With the rapid development of cloud computing, Internet of things and other advanced technologies and the challenges facing the manufacturing industry, cloud manufacturing models and technologies emerge as the times require, the core of which is to realize the coordination and sharing of manufacturing resources. It provides a new impetus for the upgrading and transformation of manufacturing industry. However, due to the openness and multi-user characteristics of cloud manufacturing mode, the multi-user task execution process involves the heterogeneity of manufacturing tasks. The competitiveness of task resource service, state monitoring and evaluation after task execution are discussed. In this paper, the optimal execution of manufacturing tasks in cloud manufacturing mode is studied from four aspects. And take the building materials equipment enterprise as the application object to carry on the practice research. The main research work may be summarized as follows: 1) aiming at the problem of task heterogeneity in manufacturing task execution, the information model and semantic modeling framework of cloud manufacturing task are proposed. Firstly, the initial cloud manufacturing task ontology (OCMT Ontology) is established by using ontology modeling technology, which is based on the document library of manufacturing tasks of building materials and equipment enterprises combined with text processing technology. The general-purpose cloud manufacturing task ontology GCMT ontology is established and perfected by ontology self-learning model. On this basis, the semantic description of cloud manufacturing tasks is realized by matching GCMT Ontology and constructing the cloud manufacturing task sub-ontology (CMTS _ S _ T _ ontology). In this paper, a framework for constructing cloud manufacturing task execution service chain is proposed. Based on the analysis of single user resource service optimization, the multi-user task resource service optimization model is studied. Aiming at the competition between multi-user and resource service, a game model of multi-user resource service is proposed by applying evolutionary game theory. According to whether the task is delayed or not, the evolutionary stability strategy of the game model is solved in four types, and the evolutionary phase diagram of the dynamic replication equation is analyzed. According to the temporal logic relation of manufacturing sub-task, the executable collaborative manufacturing resource service chain is constructed. Thirdly, a framework for monitoring the state of task execution process in cloud manufacturing mode is proposed, and a consistent mapping model of multi-source data based on manufacturing task sub-ontology is constructed. According to the structure of manufacturing task and the chain of execution service, the data fusion of task execution progress is realized. According to the data of real-time monitoring of manufacturing resources, the hidden Markov model is applied to realize the real-time monitoring of manufacturing resources. Finally, the evaluation model of cloud manufacturing task execution process is proposed. The evaluation index and fuzzy processing method of different execution stages are established, and the intuitionistic fuzzy OWA-TOPSIS method is proposed to evaluate the task execution process. Six different kinds of TOPSIS data accumulation methods and identification methods of best and worst ideal points are constructed, and the practicability of the proposed method is verified by a case study. Based on the practical application, the task execution process management system in cloud manufacturing mode is developed for the manufacturing process of building materials and equipment manufacturing enterprises. Task execution planning management, process tracking and evaluation are implemented among multiple enterprises in collaborative manufacturing.
【學(xué)位授予單位】：武漢理工大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2013
【分類號(hào)】：TU506

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