Study on the Combination of SOM and K-Means Algorithms in Manufacturing Process Quality Control

Yi Bing Li; Fei Pan

doi:10.4028/www.scientific.net/AMM.427-429.1315

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 427-429Study on the Combination of SOM and K-Means...

Study on the Combination of SOM and K-Means Algorithms in Manufacturing Process Quality Control

Abstract:

Nowadays, customers are seeking products of high quality and low cost. The use of neural networks in quality control has been a popular research topic over the last decade. An adaptive self-organizing mapping (SOM) neural network algorithm is proposed to overcome the shortages of traditional neural networks in this paper. In order to improve the classification effectiveness of SOM neural network, this paper designs an improved SOM neural network, which combined the SOM and K-means algorithms. The flow of combination of SOM and K-means algorithms was analyzed in this paper. And the case study of cement slide shoe bearing in manufacturing process was also given to illustrate the feasible and effective.

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Periodical:

Applied Mechanics and Materials (Volumes 427-429)

Pages:

1315-1318

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.427-429.1315

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Online since:

September 2013

Authors:

Yi Bing Li*, Fei Pan

Keywords:

Combination Algorithm, K-Means Algorithm, Manufacturing Process Quality Control, Self-Organizing Mapping (SOM)

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References

[1] Jianbo Yu, Lifeng Xi. Using MQE Chart Based on Self-Organizing Map Neural Network for Monitoring Out-of-control Signals in Manufacturing Processes[J]. International Journal of Production Research, 2008, vol46, no21: 5907–5933.

DOI: 10.1080/00207540701358729

Google Scholar

[2] Wang Hai-yu. Statistical quality monitoring of multiple steps delay feedback controlled process[J]. Systems Engineering – Theory & Practice, 2011, vol31, no1: 138-143.

Google Scholar

[3] M. Lópeza, S. Valero, C. Senabre, J. Aparicio, A. Gabaldon. Application of SOM neural networks to short-term load forecasting: The Spanish electricity market case study[J]. Electric Power Systems Research, 2012, no91: 18-27.

DOI: 10.1016/j.epsr.2012.04.009

Google Scholar

[4] REN Jun-hao, JI Pei-qi, GENG Yu. Application and improvement of SOM network in remote sensing image classification[J]. Application Research of Computers, 2011, vol28, no3: 1170-1173.

Google Scholar

[5] Belzarena, Pablo; Aspirot, Laura. End-to-end quality of service seen by applications: A statistical learning approach[J]. Computer Networks, 2010, vol54, n17: 3123-3143.

DOI: 10.1016/j.comnet.2010.06.004

Google Scholar

[6] El-Midany, T.T.; El-Baz, M.A.; Abd-Elwahed, M.S. A proposed framework for control chart pattern recognition in multivariate process using artificial neural networks[J]. Expert Systems with Applications, 2010, vol37, no2, 1035-1042.

DOI: 10.1016/j.eswa.2009.05.092

Google Scholar

[7] Pan Fei. Study and Application of Process Quality Control Method for Textile Machine and Manufacturing Enterprises[D]. Wuhan University of Technology, (2013).

Google Scholar