@article{(Open Science Index):https://publications.waset.org/pdf/9997463,
	  title     = {A Spatial Point Pattern Analysis to Recognize Fail Bit Patterns in Semiconductor Manufacturing},
	  author    = {Youngji Yoo and  Seung Hwan Park and  Daewoong An and  Sung-Shick Kim and  Jun-Geol Baek},
	  country	= {},
	  institution	= {},
	  abstract     = {The yield management system is very important to produce high-quality semiconductor chips in the semiconductor manufacturing process. In order to improve quality of semiconductors, various tests are conducted in the post fabrication (FAB) process. During the test process, large amount of data are collected and the data includes a lot of information about defect. In general, the defect on the wafer is the main causes of yield loss. Therefore, analyzing the defect data is necessary to improve performance of yield prediction. The wafer bin map (WBM) is one of the data collected in the test process and includes defect information such as the fail bit patterns. The fail bit has characteristics of spatial point patterns. Therefore, this paper proposes the feature extraction method using the spatial point pattern analysis. Actual data obtained from the semiconductor process is used for experiments and the experimental result shows that the proposed method is more accurately recognize the fail bit patterns.
},
	    journal   = {International Journal of Industrial and Manufacturing Engineering},
	  volume    = {8},
	  number    = {2},
	  year      = {2014},
	  pages     = {465 - 469},
	  ee        = {https://publications.waset.org/pdf/9997463},
	  url   	= {https://publications.waset.org/vol/86},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 86, 2014},
	}