制造云服务组合柔性的四维属性测度方法

doi:10.12005/orms.2015.0222

运筹与管理 ›› 2015, Vol. 24 ›› Issue (6): 272-280.DOI: 10.12005/orms.2015.0222

制造云服务组合柔性的四维属性测度方法

徐宣国^1,2, 张凯², 苏翔², 刘开²

1.山东农业大学经济管理学院,山东泰安 271018;
2.江苏科技大学经济管理学院,江苏镇江 212003

收稿日期:2014-09-03 出版日期:2015-12-25
作者简介:徐宣国(1978-),男,山东日照人,副教授、博士,研究方向:企业管理。
基金资助:
国家自然科学基金资助项目(71371088,71471078,71331003);江苏省青蓝工程

Four-attributes Measurement Method of Cloud Service Composition Flexibility

XU Xuan-guo^1,2, ZHANG Kai², SU Xiang², LIU Kai²

1.School of Economics and Management, Shandong Agricultural University, Taian 271018, China;
2.School of Economics and Management, Jiangsu University of Science and Technology, Zhenjiang 212003, China

Received:2014-09-03 Online:2015-12-25

摘要/Abstract

摘要： 云制造环境下服务资源进行动态组合时不可避免地遇到内、外部环境的不确定性,这些不确定性因素直接影响到制造云服务组合的执行成本、效率和质量。为了有效提升制造云服务组合的柔性,需要对其柔性能力进行测度。在假定某待选云服务集中的各服务资源能够以不同的效率替代完成任务的基础上,建立了考虑制造云服务组合柔性的效率柔性、冗余柔性、路径柔性和任务柔性的四维属性测度方法。最后,结合具体算例对该方法的应用过程进行了分析。

关键词: 云制造, 制造云服务组合, 柔性测度, 冗余柔性

Abstract: In the process of resource service composition in the cloud manufacturing environment, inevitably there are many uncertain factors from internal and external environments influencing the dynamics of cloud service composition, which directly affect its operating cost, efficiency and quality. To effectively improve the flexibility of cloud service composition, this article needs to measure the flexibility. Based on the assumption that each resource service in the candidate cloud services set can substitute others to complete tasks with different efficiency in case of disturbance occurring, we propose a measurement method of cloud service composition flexibility. The method takes into account four attributes, including the efficient flexibility, redundancy flexibility, path flexibility and task flexibility. Finally, this cloud service composition flexibility measurement method is verified with an example to illustrate its application process.

Key words: cloud manufacturing, cloud service composition, flexibility measurement, redundancy flexibility

中图分类号:

TP391

徐宣国, 张凯, 苏翔, 刘开. 制造云服务组合柔性的四维属性测度方法[J]. 运筹与管理, 2015, 24(6): 272-280.

XU Xuan-guo, ZHANG Kai, SU Xiang, LIU Kai. Four-attributes Measurement Method of Cloud Service Composition Flexibility[J]. Operations Research and Management Science, 2015, 24(6): 272-280.

参考文献

[1] 李伯虎,张霖,等.云制造—面向服务的网络化制造新模式 [J]. 计算机集成制造系统,2010,16(1):1-7,16.
[2] 张霖,罗永亮,范文慧,等.云制造及相关先进制造模式分析[J].计算机集成制造系统,2011,17(3):458-468.
[3] Smirnov A, Sheremetov L, Sanchez C. Dynamic configuration of flexible supply networks based on semantic service composition[J]. International Journal of Production Research, 2013, 51(7): 2160-2175.
[4] Tao F, Zhao D M, Hu Y F. Resource service composition and its optimal-selection based on particle swarm optimization in manufacturing grid system[J]. IEEE Transactions on Industrial Informatics, 2008, 4(4): 315-327.
[5] 陶飞,胡业发,张霖.制造网格服务资源优化配置理论与方法[M] . 北京:机械工业出版社,2010.
[6] Lori L K, Manoj K M, Subhash S. Measuring dimensions of manufacturing flexibility[J]. Journal of Operations Management, 2004, 22: 171-196.
[7] Ebru K B, Ana M, Stephan B. Managing flexible capacity in a make-to-order environment[J]. Management Science, 2005, 51(2):167-180.
[8] Joseph O A, Sridharan R. Evaluation of routing flexibility of a flexible manufacturing system using simulation modeling and analysis[J]. International Journal of Advanced Manufacturing Technology, 2011, 56: 273-289.
[9] 陶飞,张霖,等.云制造特征及制造云服务组合关键问题研究[J].计算机集成制造系统,2011,17(3):477-486.
[10] Chryssolouris G. Manufacturing systems: theory and practice[M]. Springer, 2006.
[11] 王晶,齐京华,刘晓宇,等.生产系统柔性的度量方法研究[J]. 管理工程学报,2003,17(3):63-66.
[12] Chang A Y. An attribute approach to the measurement of machine-group flexibility[J]. European Journal of Operational Research, 2009, 194: 774-786.
[13] Wahab M I M, Wu D D, Lee C G. A generic approach to measuring the machine flexibility of manufacturing systems[J]. European Journal of Operational Research, 2008, 186: 137-149.
[14] 徐宣国,王军,高松,等.一种制造单元柔性的多属性度量方法[J]. 系统管理学报,2014,23(3):397-402.

制造云服务组合柔性的四维属性测度方法

Four-attributes Measurement Method of Cloud Service Composition Flexibility

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