面向知识管理的过程企业知识模型体系研究

• 论文 •

面向知识管理的过程企业知识模型体系研究

吉旭，朱立嘉，赵丰，唐建华

四川大学化工学院，四川成都 610065

收稿日期:2004-12-20 修回日期:2005-06-20 出版日期:2006-03-15 发布日期:2006-03-25
基金资助:
国家自然科学基金资助项目(20306017)。Foundation item:

Research on knowledge modeling system oriented to knowledge management for process enterprises

JI Xu, ZHU Li-jia, ZHAO Feng, TANG Jian-hua

Sch. of Chemical Eng., Sichuan Univ., Chengdu 610065, China

Received:2004-12-20 Revised:2005-06-20 Online:2006-03-15 Published:2006-03-25
Supported by:
Project supported by the National Natural Science Foundation, China(No.20306017).

摘要/Abstract

摘要： 过程企业由于其特定的技术经济形态，由单元生产过程和市场需求协同作用，驱动决策流成为其知识管理显著的特点和难点。分析了过程企业由动态过程模拟模型、过程控制模型、技术经济评价及经营决策模型构成的三级过程性知识模型体系，提出静态性知识、策略性知识和推理性知识的知识分类方法，解决了过程企业实施现代集成过程系统必须的基于市场需求和生产过程的决策模型。研究并提出了基于类的面向对象的知识模型表达模式，形成由模型类、模型框架和模型实例构成的模型层次，讨论了以过程模拟和数据挖掘作为重要技术支撑的知识学习方法，并针对行业的过程性特点，提出了面向业务与决策过程的知识发布模式。

关键词: 知识管理, 知识模型, 数据挖掘, 过程企业

Abstract: Due to its unique technical & economic characteristics of process enterprises-collaboration between product units and market demand, it is difficult to implement knowledge management in process enterprises. To resolve this problem, a three-level process knowledge modeling system for process enterprises composed of dynamic process simulation model, process control model, technical & economic evaluation and management decision-making model was analyzed. Then knowledge classification method was proposed which including static knowledge, strategic knowledge and reasoning knowledge. The decision-making model based on market demand and production process was implemented in process enterprises. The model was prerequisite to modern integration process system. ,Then the object-oriented knowledge model representation based on classes was studied, which was composed of model class, model framework and model instance. Knowledge acquisition method and knowledge release mode, which was characterized by process simulation and data mining, were also discussed considering of its industrial characteristics. Several examples were given to illustrate application of the techniques.

Key words: knowledge management, knowledge model, data mining, process enterprises

中图分类号:

TP391
TP311

吉旭，朱立嘉，赵丰，唐建华. 面向知识管理的过程企业知识模型体系研究[J]. .

JI Xu, ZHU Li-jia, ZHAO Feng, TANG Jian-hua. Research on knowledge modeling system oriented to knowledge management for process enterprises[J]. .

参考文献

［1］ DEVEDZIC V. A survey of modern knowledge modeling techniques［J］. Expert Systems with Applications, 1999, 17(4)：275-294.

[2] NOH J B, LEE K C,KIM J K,et al. A Case-based reasoning approach to cognitive map-driven tacit knowledge management［J］.Expert Systems with Application, 2000, 19(4)：249-259.

[3] HERSCHEL R T，NEMATI H. Tacit to explicit knowledge conversion: knowledge exchange protoco1s［J］.Journal of Knowledge Management，200l，5(1)：107-l16.

[4] HAI Z. A knowledge grid model and platform for global knowledge sharing［J］.Expert Systems with Applications, 2002, 22(4)：313-320.

[5] PAN Xuwei, GU Xinjian,QIU Yuanfu,et al.Knowledge modeling techniques for knowledge management［J］.Computer Integrated Manufacturing Systems,2003,9(7)：516-521(in Chinese).［潘旭伟，顾新建,仇元福，等.面向知识管理的知识建模技术［J］.计算机集成制造系统，2003，9(7)：516-521.］

[6] KANG Zhuang,FAN Zhiping. A basic framework for knowledge management based on the dual-direction Model［J］. Industry Engineering and Management, 2003,8(5):22-26(in Chinese).［康壮，樊治平. 一种基于双向模型的知识管理基础框架［J］.工业工程与管理, 2003,8(5):22-26.］

[7] XIA Hongxia, LIU Hanli. The method of hierarchical and structured mixed knowledge representation［J］. Journal of Wuhan University of Technology,1999,21(6)：25-29.(in Chinese).［夏红霞，刘汉丽.分层结构化混合知识表达方法［J］. 武汉工业大学学报, 1999, 21(6)：25-29.］

[8] MIDORI T.Integration of multiple knowledge representation for classification problems［J］.Artifical Intelligence in Engineering,1995,9(4):236-244.

[9] XIONG G，NYLEXG T R.Comparison between CIMS and CIPS［A］.Proceedings of 7th IEEE International Conference on Emerging Technologies and Factory Automation［C］.New York,NJ,USA:IEEE Corporate Standards Office,1999.409-416.

[10] LI Anxue,YANG Youqi. Intelligent management of process industry［J］. Information and Control,2003,32(3): 214-218(in Chinese).［李安学，杨友麒.过程工业企业智能管理研究［J］.信息与控制,2003,32(3)：214-218.］

[11] SHEN Hui,CHEN Yuliu. Design and development of a GDSS for enterprise integration［J］. Control and Decision, 2004,19(3)：323-330(in Chinese).［沈晖，陈禹六.面向企业集成的群体决策支持系统设计与实现［J］.控制与决策, 2004, 19(3)：323-330. ］

[12] HAN Yanling,CHEN Yun.Remote service and fault diagnosis based on data mining［J］. Computer Integrated Manufacturing Systems,2003,9(2)：158-162(in Chinese).［韩彦岭，陈云.基于数据挖掘技术的远程服务与故障诊断［J］.计算机集成制造系统,2003,9(2)：158-162.］

[13] JI Xu,ZHU Lijia. Models of cost & profit evaluation in Internet environment and instant decision［J］. Computers and Applied Chemistry, 2003,20(5):703-705(in Chinese).［吉旭，朱立嘉. 基于INTERNET的成本效益评估模型与瞬时决策［J］.计算机与应用化学, 2003,20(5):703-705.］

[14] UDO G,VINCE T.A reference model for production control in a computer integrated manufacturing environment［J］.Process Control，1994,4(4):281-290.

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