DocumentCode
3515347
Title
Study on the Quality Improvement of Injection Molding in LED Packaging Processes Based on DOE and Data Mining
Author
He Shu-guang ; Li, Li ; Qi Er-shi
Author_Institution
Sch. of Manage., Tianjin Univ., Tianjin
fYear
2007
fDate
21-25 Sept. 2007
Firstpage
6625
Lastpage
6628
Abstract
The LED (light emitting diode) packaging is a very important process between semiconductor manufacturers and the electric product manufacturers. And the injection molding process in LED packaging is critical to the quality of the final products. Based on the analysis of the injection molding processes, the main quality problems and their possible causes are studied. Then the RSM (response surface methodology) of DOE (design of experiment) is used for the optimization of the producing parameters. The optimized parameters, the mold temperature, the warm-up temperature, the screw pressure and the screw time, are found with DOE. In the running process, the CTQ (critical to quality) is controlled with SPC (Statistical process control) by different dimensions like product, product catalog, time and devices. Finally, a model of continuous quality improvement based on data mining is put forward. The association analysis is used for the parameter optimization in the running process.
Keywords
data mining; design of experiments; injection moulding; light emitting diodes; packaging; statistical process control; data mining; design of experiment; injection molding; light emitting diode packaging; mold temperature; parameter optimization; quality improvement; response surface methodology; screw pressure; statistical process control; Data mining; Fasteners; Injection molding; Light emitting diodes; Manufacturing processes; Response surface methodology; Semiconductor device manufacture; Semiconductor device packaging; Temperature; US Department of Energy;
fLanguage
English
Publisher
ieee
Conference_Titel
Wireless Communications, Networking and Mobile Computing, 2007. WiCom 2007. International Conference on
Conference_Location
Shanghai
Print_ISBN
978-1-4244-1311-9
Type
conf
DOI
10.1109/WICOM.2007.1626
Filename
4341401
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