Optimization on Hardware Inventory of the Steel Pipe Enterprise Based on Cluster-Algorithm

Zhong Qing Yang; Shao Hua Dong; Cheng Wei Li

doi:10.4028/www.scientific.net/AMM.529.595

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Optimization on Hardware Inventory of the Steel Pipe Enterprise Based on Cluster-Algorithm
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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 529Optimization on Hardware Inventory of the Steel...

Optimization on Hardware Inventory of the Steel Pipe Enterprise Based on Cluster-Algorithm

Abstract:

Based on the existing data accumulation and process of stock management of a Steel pipe enterprise, a general analysis for its current inventory structure is done, then a classification research for hardware inventory is done with the theory of cluster-algorithm. Finally, a visualizing stock query function which is the main contribution of this paper is developed based on the research above.

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Periodical:

Applied Mechanics and Materials (Volume 529)

Pages:

595-599

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.529.595

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Online since:

June 2014

Authors:

Zhong Qing Yang*, Shao Hua Dong, Cheng Wei Li

Keywords:

Classification Method, Cluster Analysis, Hardware Stock

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References

[1] Xiafang jin, optimization study of manufacturing enterprise spare parts inventory. the master's paper of tongji university. (2009).

Google Scholar

[2] Mingkun ren spare parts inventory model of vague discrete demand enterprise. compute integrated manufacturing system, 2010, vol 16 pp.15-24.

Google Scholar

[3] Xiao zhou, the procurement optimization model and implementation of process manufacturing enterprises based on time cost control. the master's paper of Harbin Institute of Technology, 2004, pp.11-36.

Google Scholar

[4] Tersime R．Econo mic purchasing strategies for temporary price discount[J]．European Journal of Operational Research, 2001, pp.328-345.

Google Scholar

[5] Hongrong zhang, feng zhang, research and improvement of the traditional k-means clustering algorithm. XianYang Normal College journal, 2001, vol 25 pp.59-62.

Google Scholar

[6] Jian yu, qiansheng cheng, the resarch of the optimal number of clusters in vague clustering method. science in china , 2002, vol 32 pp.274-280.

Google Scholar