本文選題：自適應(yīng)調(diào)度 + 混流制造　； 參考：《廣東工業(yè)大學(xué)》2013年博士論文

【摘要】：混流制造是一種以客戶需求為導(dǎo)向、在當(dāng)前大批量定制生產(chǎn)中的常見生產(chǎn)組織模式。其生產(chǎn)訂單存在多品種、周期性、數(shù)量多變等特點,但生產(chǎn)過程資源需求模型相對固定。混流制造過程不可避免存在諸多不確定的動態(tài)事件,如設(shè)備故障、緊急插單、質(zhì)量事故等,導(dǎo)致生產(chǎn)過程無法遵循預(yù)定義的基準(zhǔn)計劃執(zhí)行。因此對混流制造采取合理的動態(tài)調(diào)度機(jī)制,以消除動態(tài)事件對計劃執(zhí)行的影響,保持制造過程的穩(wěn)定性,成為一個重要科學(xué)問題。 然而,目前對動態(tài)調(diào)度的研究多集中在一個理想模型下的調(diào)度理論研究,其隨機(jī)事件的加入也大多基于某種理論模型,沒有考慮車間信息反饋斷層的問題,缺乏在實際應(yīng)用中的技術(shù)支撐環(huán)境,在實際應(yīng)用中無法應(yīng)對車間現(xiàn)場的瞬息萬變。隨著物聯(lián)網(wǎng)技術(shù)飛速發(fā)展,實時制造環(huán)境下的自適應(yīng)調(diào)度,具備了實現(xiàn)的技術(shù)基礎(chǔ)。 本論文在國家基金“基于RFID的分時段雙層實時動態(tài)OKP調(diào)度理論模型與算法研究(61074146)”支持下,基于制造物聯(lián)網(wǎng)實時制造環(huán)境,對混流制造過程在實時反饋條件下的自適應(yīng)調(diào)度方法進(jìn)行了研究。 論文的具體研究內(nèi)容如下： 1)、針對目前我國中小企業(yè)制造車間存在的信息斷層問題,構(gòu)建了一個基于制造物聯(lián)網(wǎng)技術(shù)的實時制造系統(tǒng)的框架,為后續(xù)混流過程的自適應(yīng)調(diào)度研究提供了技術(shù)基礎(chǔ)。在此框架下,采用了統(tǒng)一接口構(gòu)建了RFID中間件實現(xiàn)了Multi-Agent封裝模式下RFID對象的即插即用接入。然后設(shè)計了一個基于RFID-Bus的實時消息處理模式,實現(xiàn)了實時制造消息的處理和反饋統(tǒng)一機(jī)制�；诖藱C(jī)制,構(gòu)建了一個兩級RFID-Bus的實時制造系統(tǒng)環(huán)境及其在企業(yè)制造車間的部署方法。 2)、針對混流制造系統(tǒng)規(guī)模龐大,難以求解的難題,提出了一個基于ROPN的制造系統(tǒng)MPN建模機(jī)制,給出了具體的建模流程和方法,縮小了混流制造系統(tǒng)模型規(guī)模。論文先分析了混流制造過程帶轉(zhuǎn)運／緩存約束的非等價并聯(lián)機(jī)制造的特點,通過將等價并行機(jī)建模成一個資源提供節(jié)點,提出了一種基于制造系統(tǒng)資源建模方法和建模流程。定義了MPN (Manufacturing Petri Net)模型,在模型中闡述了基于實時制造物聯(lián)網(wǎng)中智能令牌在模型中映射的知識函數(shù),及路徑查找辦法。 3)、構(gòu)建了混流制造系統(tǒng)MPN模型后,對MPN中非等價并聯(lián)機(jī)調(diào)度問題進(jìn)行了分析,針對混流模型中并聯(lián)機(jī)調(diào)度難題,構(gòu)建了一個通過調(diào)度變遷觸發(fā)順序來進(jìn)行作業(yè)調(diào)度的離線調(diào)度方案,并給出了基于MMAS的蟻群算法的優(yōu)化方法,并采用田口實驗設(shè)計方法對算法中的參數(shù)最優(yōu)配置進(jìn)行了探求,形成了制造系統(tǒng)執(zhí)行的基準(zhǔn)計劃。 4)、針對基準(zhǔn)計劃在MPN中的執(zhí)行,首先分析了實時制造環(huán)境下大規(guī)模定制混流制造過程的動態(tài)事件的特點,并將動態(tài)事件在MPN中統(tǒng)一映射為資源提供能力的失能事件。根據(jù)實時制造環(huán)境的特點,采用修正式策略,構(gòu)建了一個計劃與執(zhí)行交互的在線自適應(yīng)調(diào)度的框架。在這個框架中,通過樹結(jié)構(gòu)的決策單元,實時監(jiān)控制造系統(tǒng)MPN中各作業(yè)的執(zhí)行偏離度,根據(jù)偏離度分布情況進(jìn)行實時修正。然后,根據(jù)決策樹結(jié)構(gòu)特點,提出了一個基于層級反饋的在線調(diào)度方法,并對在線調(diào)度方法進(jìn)行了實現(xiàn)。 5)、根據(jù)論文提出的自適應(yīng)調(diào)度框架和理論,開發(fā)了一套自適應(yīng)調(diào)度仿真系統(tǒng),對制造系統(tǒng)進(jìn)行了仿真和推演,對算法有效性進(jìn)行了驗證。 案例測試結(jié)果表明,本論文提出基于制造物聯(lián)網(wǎng)實時制造環(huán)境的自適應(yīng)調(diào)度方法,在某些動態(tài)事件模式下,可以有效的消除其對制造系統(tǒng)的影響,提高車間生產(chǎn)效率,驗證了論文工作的合理性。 本論文研究內(nèi)容還有許多不足之處需要不斷完善和改進(jìn),有待今后進(jìn)一步研究。
[Abstract]:Mixed flow manufacturing is a kind of common production organization pattern which is guided by customer ' s demand . It has many characteristics such as many varieties , periodicity , quantity and so on , but the production process resources demand model is relatively fixed . There are many uncertain dynamic events such as equipment failure , emergency plug - in , quality accident and so on , which can lead to the production process not to follow predefined benchmark plan execution . Therefore , the process of mixed flow is reasonably dynamic scheduling mechanism to eliminate the effect of dynamic event on the plan execution , and maintain the stability of manufacturing process and become an important scientific problem .

However , the researches on dynamic scheduling are mostly focused on the scheduling theory under an ideal model , and the random events are mostly based on a certain theoretical model , and the problems of the workshop information feedback faults are not taken into consideration , and the technology support environment in the practical application is not taken into account .

Based on the real - time manufacturing environment of Internet of manufacture , this paper studied the adaptive scheduling method under real - time feedback condition based on the real - time manufacturing environment .

The contents of the thesis are as follows :

1 ) In order to solve the problem of information faults existing in the manufacturing workshop of small and medium - sized enterprises in China , a frame of real - time manufacturing system based on Internet of manufacture technology is constructed , which provides a technical basis for the adaptive scheduling of the subsequent mixed - flow process .

In this paper , an MPN modeling mechanism based on ROPN is proposed to reduce the size of the mixed - stream manufacturing system .

3 ) After constructing the MPN model of the mixed - stream manufacturing system , the problem of non - equivalent and online scheduling of MPN is analyzed . According to the problem of online scheduling in the mixed - flow model , an off - line scheduling scheme for job scheduling is constructed by scheduling the transition triggering sequence , and an optimization method of the ant colony algorithm based on MMAS is constructed , and the optimal allocation of parameters in the algorithm is explored by using the field - port experiment design method , and a reference plan for the execution of the manufacturing system is formed .

4 ) According to the implementation of the benchmark plan in MPN , firstly , the characteristics of the dynamic event of mass customization mixed - stream manufacturing process in real - time manufacturing environment are analyzed , and the dynamic events are uniformly mapped into the power - loss events of resources in MPN . According to the characteristics of real - time manufacturing environment , a plan and execution interaction - based on - line adaptive scheduling framework is built . In this framework , a hierarchical feedback based on - line scheduling method is proposed based on the characteristics of decision tree structure , and the on - line scheduling method is realized .

5 ) According to the adaptive scheduling framework and theory proposed by the paper , an adaptive scheduling simulation system is developed , and the simulation and deduction of the manufacturing system are carried out , and the validity of the algorithm is verified .

The case test results show that the self - adaptive scheduling method based on the real - time manufacturing environment of the manufacturing internet of things can effectively eliminate the influence on the manufacturing system under certain dynamic event modes , improve the production efficiency of the workshop and verify the rationality of the work of the paper .

There are many deficiencies that need to be perfected and improved , and further research is to be done in the future .
【學(xué)位授予單位】：廣東工業(yè)大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2013
【分類號】：TH186

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 臧傳真,范玉順;無線傳感器網(wǎng)絡(luò)中信息獲取關(guān)鍵問題的研究[J];傳感器技術(shù);2005年09期

2 戴青云;羅天友;;基于RFID的在制品追蹤與管理系統(tǒng)[J];電腦與電信;2006年07期

3 黃剛;邵新宇;饒運清;;多目標(biāo)混流裝配計劃排序問題[J];華中科技大學(xué)學(xué)報(自然科學(xué)版);2007年10期

4 劉瓊;劉煒琪;張超勇;;基于GA-PSO的多目標(biāo)混流裝配線排序研究[J];華中科技大學(xué)學(xué)報(自然科學(xué)版);2011年10期

5 嵇文路;夏安邦;;基于eEPC和UML的企業(yè)建模[J];計算機(jī)工程;2008年08期

6 郜慶路,羅欣,楊叔子;基于螞蟻算法的混流車間動態(tài)調(diào)度研究[J];計算機(jī)集成制造系統(tǒng)-CIMS;2003年06期

7 臧傳真;范玉順;;基于智能物件的制造企業(yè)信息系統(tǒng)研究[J];計算機(jī)集成制造系統(tǒng);2007年01期

8 蘇平;于兆勤;;基于混合遺傳算法的混合裝配線排序問題研究[J];計算機(jī)集成制造系統(tǒng);2008年05期

9 張沙清;陳新度;陳慶新;陳新;;資源不確定環(huán)境下模具多項目預(yù)測—反應(yīng)式調(diào)度算法[J];計算機(jī)集成制造系統(tǒng);2010年12期

10 劉瓊;王文璽;張超勇;朱海平;;基于改進(jìn)分散搜索的混流裝配線排序問題[J];計算機(jī)集成制造系統(tǒng);2011年04期

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