信息物理系統(tǒng)環(huán)境下面向多層次資源協(xié)同的制造智能方法
發(fā)布時間:2018-03-23 22:28
本文選題:制造智能 切入點(diǎn):多層次資源協(xié)同 出處:《科技進(jìn)步與對策》2017年17期
【摘要】:信息物理系統(tǒng)(Cyber-physical system,CPS)在制造過程中的應(yīng)用,能夠?qū)⑵髽I(yè)不同層次的制造資源連接起來,實(shí)現(xiàn)資源的按需使用和高效的過程監(jiān)控。在CPS環(huán)境下,可通過整合多粒度社會化制造資源,構(gòu)建基于動態(tài)服務(wù)聯(lián)盟的靈活多Agent制造系統(tǒng)。隨著系統(tǒng)的運(yùn)營和聯(lián)盟演化,實(shí)時制造智能方法成為解決任務(wù)分配、實(shí)時決策等問題的關(guān)鍵技術(shù)。在對多Agent制造系統(tǒng)服務(wù)能力和協(xié)同關(guān)系進(jìn)行分析的基礎(chǔ)上,提出了動態(tài)的協(xié)同任務(wù)分配模型?紤]制造任務(wù)的關(guān)系、時空等因素,構(gòu)建了基于Petri-net和多領(lǐng)域矩陣的協(xié)同任務(wù)節(jié)拍控制模型。根據(jù)智能服務(wù)單元的特點(diǎn),提出了多層次實(shí)時決策體系,分析了本地Agent的決策模型和不同企業(yè)或同一企業(yè)多Agent的協(xié)同決策機(jī)制。最后,在對實(shí)時制造智能一般框架進(jìn)行闡述的基礎(chǔ)上,提出了制造智能方法的未來研究方向和挑戰(zhàn)。
[Abstract]:The application of information physics system (CPS) in manufacturing process can connect the manufacturing resources of different levels of enterprises, and realize the on-demand use of resources and efficient process monitoring. In the CPS environment, the multi-granularity socialized manufacturing resources can be integrated. A flexible multi-#en0# manufacturing system based on dynamic service alliance is constructed. With the operation of the system and the evolution of the alliance, the intelligent method of real-time manufacturing becomes the solution of task allocation. Based on the analysis of service capability and collaborative relationship of multi-#en0# manufacturing system, a dynamic collaborative task allocation model is proposed, which considers the relationship between manufacturing tasks, time and space, and so on. Based on the characteristics of intelligent service unit, a multi-level real-time decision-making system is proposed, which is based on Petri-net and multi-domain matrix. The decision model of local Agent and the cooperative decision-making mechanism of multiple Agent in different enterprises or the same enterprise are analyzed. Finally, based on the general framework of real-time manufacturing intelligence, the future research direction and challenges of manufacturing intelligent methods are proposed.
【作者單位】: 合肥工業(yè)大學(xué)管理學(xué)院;
【基金】:國家自然科學(xué)基金重點(diǎn)項(xiàng)目(71531008);國家自然科學(xué)基金面上項(xiàng)目(71271073)
【分類號】:F274
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本文編號:1655495
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