协同制造资源集成与优化配置方法研究
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摘要
协同制造是适应网络经济和知识经济的先进制造模式,它强调企业间的协作和全社会范围内的资源共享,并以此实现产品设计制造的低成本和高效率的目标。因此,通过网络将分散在各个企业中的制造资源实现共享和优化利用是协同制造模式的重要特征之一,构建能集成多方面资源、具有多种功能的资源集成平台将成为协同制造的一种重要技术使能工具,可以有效地支持企业实施协同制造。
本文针对协同制造资源集成与优化配置问题,从集成平台体系结构、制造资源集成框架、制造资源建模方法、制造资源优化配置方法以及系统实现等几个方面进行了研究。
参考网格的运行机制,建立了基于网格的协同制造资源集成平台体系结构。该平台包括制造资源管理系统、制造资源优化配置系统和面向网格的协同工具。
通过分析国内外制造资源集成的研究现状,建立了基于Web Services的协同制造资源集成框架,采用Web本体语言(OWL)进行制造资源建模。
针对协同制造的特点,提出了协同制造资源优化配置的两级优化配置策略:面向生产任务的制造伙伴优选与面向制造加工阶段的物理制造单元优选。对于制造伙伴优选,给出了制造伙伴选择综合评价参考体系,提出了基于神经网络的制造伙伴选择模型,采用基于连接结构优化的粒子群优化算法(SPSO)实现了制造伙伴优选。对于物理制造单元优选,利用逻辑加工路线(LMP)和逻辑制造单元(LMU)描述协同制造任务,以时间、质量、成本为目标建立数学模型,用遗传算法(GA)实现了物理制造单元优选。
最后,开发了协同制造资源集成平台的原型系统,主要包括用户注册、制造资源管理和制造资源优化配置三个功能模块。通过典型算例证明,该系统可以有效地集成制造资源,解决协同制造资源优化配置问题效果良好。
As a kind of advanced manufacturing paradigm in network economy and knowledge economy environment, collaborative manufacturing (CM) emphasizes inter-enterprise collaboration and resources sharing in the whole society. The goal of CM is to realize the lower cost and higher efficiency of product designing and manufacturing process. Therefore, the share and optimized utilization of manufacturing resources dispersing in enterprises through network is one of important characteristics of CM. The resources integration platform that can integrate all kinds of resources and provide all kinds of functions will become one of important technically enabled tools for CM, and will effectively support implementation of CM in enterprises.
In this thesis, the manufacturing resources integration problem in CM environment is discussed, including the architecture of integration platform, manufacturing resources integration framework, manufacturing resources modeling method, manufacturing resources optimized configuration method, and system realization.
With reference to operation mechanism of grid, a grid-based CM resources integration architecture is proposed which consist of manufacturing resources management system, and manufacturing resources optimized configuration system.
Based on analysis of current situation in manufacturing resources integration, a resources integration framework based on Web Services is presented, and the web ontology language (OWL) is chosen to describe manufacturing resources.
According to the characteristic of CM, the two levels optimized strategy of manufacturing resources optimized configuration is proposed, which are the optimization of manufacturing partners and the optimization of Physical Manufacturing Unit (PMU). For optimization of manufacturing partners, a multiple attributes evaluation system of partner selection is presented, the artificial neural network trained by a Structure-improving particle swarm optimization algorithm is proposed to solve the problem. For optimization of PMU, LMP (logical manufacturing process) and LMU (logical manufacturing unit) are used to describe collaborative manufacturing task, an improved algorithm based on GA is proposed to solve the problem.
Finally, the prototype system of CM resources integration platform is developed, it contains three modules: user register, manufacturing resources management and manufacturing resources optimized configuration.
本文针对协同制造资源集成与优化配置问题,从集成平台体系结构、制造资源集成框架、制造资源建模方法、制造资源优化配置方法以及系统实现等几个方面进行了研究。
参考网格的运行机制,建立了基于网格的协同制造资源集成平台体系结构。该平台包括制造资源管理系统、制造资源优化配置系统和面向网格的协同工具。
通过分析国内外制造资源集成的研究现状,建立了基于Web Services的协同制造资源集成框架,采用Web本体语言(OWL)进行制造资源建模。
针对协同制造的特点,提出了协同制造资源优化配置的两级优化配置策略:面向生产任务的制造伙伴优选与面向制造加工阶段的物理制造单元优选。对于制造伙伴优选,给出了制造伙伴选择综合评价参考体系,提出了基于神经网络的制造伙伴选择模型,采用基于连接结构优化的粒子群优化算法(SPSO)实现了制造伙伴优选。对于物理制造单元优选,利用逻辑加工路线(LMP)和逻辑制造单元(LMU)描述协同制造任务,以时间、质量、成本为目标建立数学模型,用遗传算法(GA)实现了物理制造单元优选。
最后,开发了协同制造资源集成平台的原型系统,主要包括用户注册、制造资源管理和制造资源优化配置三个功能模块。通过典型算例证明,该系统可以有效地集成制造资源,解决协同制造资源优化配置问题效果良好。
As a kind of advanced manufacturing paradigm in network economy and knowledge economy environment, collaborative manufacturing (CM) emphasizes inter-enterprise collaboration and resources sharing in the whole society. The goal of CM is to realize the lower cost and higher efficiency of product designing and manufacturing process. Therefore, the share and optimized utilization of manufacturing resources dispersing in enterprises through network is one of important characteristics of CM. The resources integration platform that can integrate all kinds of resources and provide all kinds of functions will become one of important technically enabled tools for CM, and will effectively support implementation of CM in enterprises.
In this thesis, the manufacturing resources integration problem in CM environment is discussed, including the architecture of integration platform, manufacturing resources integration framework, manufacturing resources modeling method, manufacturing resources optimized configuration method, and system realization.
With reference to operation mechanism of grid, a grid-based CM resources integration architecture is proposed which consist of manufacturing resources management system, and manufacturing resources optimized configuration system.
Based on analysis of current situation in manufacturing resources integration, a resources integration framework based on Web Services is presented, and the web ontology language (OWL) is chosen to describe manufacturing resources.
According to the characteristic of CM, the two levels optimized strategy of manufacturing resources optimized configuration is proposed, which are the optimization of manufacturing partners and the optimization of Physical Manufacturing Unit (PMU). For optimization of manufacturing partners, a multiple attributes evaluation system of partner selection is presented, the artificial neural network trained by a Structure-improving particle swarm optimization algorithm is proposed to solve the problem. For optimization of PMU, LMP (logical manufacturing process) and LMU (logical manufacturing unit) are used to describe collaborative manufacturing task, an improved algorithm based on GA is proposed to solve the problem.
Finally, the prototype system of CM resources integration platform is developed, it contains three modules: user register, manufacturing resources management and manufacturing resources optimized configuration.
引文
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[2] Steven Vogel, Karl Messer. Web-Enable Collaborative Manufacturing Execution System. iTAC Software Inc, 2001.1～10
[3] MESA International. Collaborative Manufacturing Explained. MESA International White Paper [EB/OL ]. http://www.mesa.org, 2003
[4] Carla Macario. The Behavior of Manufacturing Firms Under the New Economic Model. World Development, 2000, 28(9):1597～1610
[5]盛步云.企业集成化动态制造资源建模.武汉汽车工业大学学报,2000,22(2):19～21
[6]马鹏举,陈剑虹,卢秉恒等.支持动态联盟的制造资源信息建模.中国机械工程,2000, 11(7):780～782
[7]赵骥,乐清洪,朱名锉.虚拟环境下制造资源的数字化模式表达与控制.机械科学与技术,2000, 19(4):674～676
[8]刘勇,江平宇.基于Web的远程制造资源建模及其实现框架.系统仿真学报,2002, 14(10):1333～1336
[9]倪中华,易红,汤文成等.基于XML面向工艺设计的制造资源模型.计算机集成制造系统-CIMS, 2002,8(6):429～432
[10] Liu Chengying, Wang Xiankui, He Yuchen. Research on Manufacturing Resource Modeling based on the O-O method. Journal of Materials Processing Technology, 2003, 139: 40～43
[11]石旭东,李峰,李军等.面向可制造性评价的虚拟制造资源建模.中国机械工程,2002, 13(17):1483～1486
[12]胡长建,郑力,李志忠等.基于XML的自适应网络化制造资源管理系统.机械科学与技术,2003, 22(2):305～308
[13]戈鹏,殷国富,高伟.基于知识的制造资源建模与应用.中国机械工程,2003,14(17):1478～1481
[14]刘勇,江平宇,赵刚.网络化制造环境下虚拟遥现驱动的制造资源建模研究.计算机辅助设计与图形学学报,2003, 15(3):362～367
[15] Talluri S, Baker R C. A quantitative framework for designing efficient business process alliances [A]. International Conference on Engineering Management and Control ( IEMC) [C], 1996: 656～661
[16] Satty T. L..层次分析法:在资源分配、管理和冲突分析中的应用.许数柏译,北京:煤炭工业出版社,1988.35～39
[17]施战备,俞涛,刘丽兰.制造网格及其资源配置算法.计算机工程,2004, 30(5):117～119
[18]赵刚,江平宇.网络化制造中资源优化配置的方法研究.新工艺新技术新设备, 2003,33(8):60～64
[19]李培根,张洁.敏捷化智能制造系统的重构与控制.北京:机械工业出版社,2003.79～96
[20]董文辉,巩亚东,王宛山.基于遗传算法的网络化制造伙伴选择与优化.东北大学学报,2005,26(5):474～477
[21]马雪芬,戴旭东,孙树栋.面向网络化制造的制造资源优化配置研究.计算机集成制造系统-CMIS,2004,10(5):523～527
[22]冯尉东,陈剑,赵纯均.基于遗传算法的动态联盟伙伴选择过程及优化模型.清华大学学报(自然科学版),2000,40(10):120～124
[23]李泽彪.面向协同生产的供应链构建系统研究与开发[硕士学位论文].杭州:浙江大学,2004.5～6
[24]单汨源,彭忆,高阳.一种协同生产管理实现模式.中国机械工程,2002,11(7):773～776
[25]范玉顺,刘飞,祁国宁.网络化制造系统及其应用实践.北京:机械工业出版社,2003.213～219
[26] ESPRIT Consortium AMICE. CIMOSA: Open System Architecture for CIM. Springer-Verlag, 1993
[27] CCE-CNMA Consortium. CCE-CNMA: An Integration Platform for Distributed Manufacturing Application. Berlin, Germany: Springer-Verlag, 1995
[28] Weston, R.H. Steps towards enterprise-wide integration: a definition of need and first-generation open solutions. International Journal of Production Research, 31(9): 2235～2254
[29] Brunt, R., Hutt, A. OPEN framework-The systems Architecture: an introduction. New York: Prentice Hall, 1992
[30]范玉顺,吴澄,俞盘祥.面向CIMS制造业的应用集成平台.清华大学学报,1998,38(3):104～107
[31] Foster I., Kesselman C.. The Grid: Blueprint for a New Computing Infrastructure. http://www.gridforum.org/
[32] Foster I.. http://www-fp.mcs.anl.gov/～foster/Talks/GridTutorial.ppt
[33] Foster I., Kesselman C.. Globus: A Metacomputing Infrastructure Toolkit. International Journal of Supercomputer Applications, 1997, 11 (2):115～128
[34] Grid Forum HomePage. http://www.globalgridforum.com/
[35] Foster I., Kesselman C., Tuecke S.. The anatomy of the grid:enabling scalable virtual organizations. International Journal High - Performance Computing Applications, 2001, 15 (3): 200～221
[36] Foster I.. What is the Grid? A Three Point Checklist. http://www.gridforum.org/
[37]都志辉.网格计算:是宏伟蓝图还是海市屡楼.http://www.gridhom.com
[38] Donald McMullen, Randall Bramley, et al. Xport Collaboratory for X-ray Crystallography, http://www.iumsc.indiana.edu/XPort/xport_demo_talk.pdf
[39] CoG Kit Homepage, http://www.globus.org/cog/
[40] Science Portals Project, http://www.extreme.indiana.edu/an/
[41] Gabrielle Allen. Cactus Grid Computing, http://www.cactuscode.org/Presentations/Europar_August01.ppt
[42] Ian Foster, Carl Kesselman, Jeffrey M. et al. The Physiology of the Grid-An Open Grid Services Architecture for Distributed Systems Integration. http://www.unix.globus.org/toolkit/3.0/ogsa/docs/physiology.pdf, 2001.8～9
[43]张立晴,范玉顺.网格技术及其在制造领域的应用.航空制造技术,2003,(2) :32～37
[44] Fan Yushun, Zhao Dazhe. Manufacturing grids: needs, concept, and architecture [A]. GCC 2003, LNCS 3032[C]. Heidelberg, Berlin: Springer-Verlag, 2004.653～656
[45] Liu Lilan, Yu Tao, Shi Zhanbei, et al. Resource management and scheduling in manufacturing grid [A]. GCC 2003, LNCS 3033[C]. Heidelberg, Berlin: Springer-Verlag, 2004.137～140
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