2014 ApplyingDataMiningTechniquestoA

• (Zheng et al., 2014) ⇒ Li Zheng, Chunqiu Zeng, Lei Li, Yexi Jiang, Wei Xue, Jingxuan Li, Chao Shen, Wubai Zhou, Hongtai Li, Liang Tang, Tao Li, Bing Duan, Ming Lei, and Pengnian Wang. (2014). “Applying Data Mining Techniques to Address Critical Process Optimization Needs in Advanced Manufacturing.” In: Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2014) Journal. ISBN:978-1-4503-2956-9 doi:10.1145/2623330.2623347

Subject Headings:

Cited By

• http://scholar.google.com/scholar?q=%222014%22+Applying+Data+Mining+Techniques+to+Address+Critical+Process+Optimization+Needs+in+Advanced+Manufacturing
• http://dl.acm.org/citation.cfm?id=2623330.2623347&preflayout=flat#citedby

Quotes

Author Keywords

• Advanced manufacturing; big data; data mining; data mining platform; miscellaneous; process optimization

Abstract

Advanced manufacturing such as aerospace, semi-conductor, and flat display device often involves complex production processes, and generates large volume of production data. In general, the production data comes from products with different levels of quality, assembly line with complex flows and equipments, and processing craft with massive controlling parameters. The scale and complexity of data is beyond the analytic power of traditional IT infrastructures. To achieve better manufacturing performance, it is imperative to explore the underlying dependencies of the production data and exploit analytic insights to improve the production process. However, few research and industrial efforts have been reported on providing manufacturers with integrated data analytical solutions to reveal potentials and optimize the production process from data-driven perspectives.

In this paper, we design, implement and deploy an integrated solution, named PDP-Miner, which is a data analytics platform customized for process optimization in Plasma Display Panel (PDP) manufacturing. The system utilizes the latest advances in data mining technologies and Big Data infrastructures to create a complete analytical solution. Besides, our proposed system is capable of supporting automatically configuring and scheduling analysis tasks, and balancing heterogeneous computing resources. The system and the analytic strategies can be applied to other advanced manufacturing fields to enable complex data analysis tasks. Since 2013, PDP-Miner has been deployed as the data analysis platform of ChangHong COC. By taking the advantages of our system, the overall PDP yield rate has increased from 91% to 94%. The monthly production is boosted by 10,000 panels, which brings more than 117 million RMB of revenue improvement per year.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2014 ApplyingDataMiningTechniquestoA	Lei Li Tao Li Li Zheng Chao Shen Liang Tang Chunqiu Zeng Yexi Jiang Wei Xue Jingxuan Li Wubai Zhou Hongtai Li Bing Duan Ming Lei Pengnian Wang			Applying Data Mining Techniques to Address Critical Process Optimization Needs in Advanced Manufacturing				10.1145/2623330.2623347		2014