【摘 要】
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With the availability of advanced sensing technology, product and process quality nowadays are often assessed and characterized by observations with complex
【机 构】
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ShanghaiJiaotongUniversity
【出 处】
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The Third IMS-China International Conference on Statistics a
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With the availability of advanced sensing technology, product and process quality nowadays are often assessed and characterized by observations with complex structures such as measurements from a 2-D surface instead of a single or multiple numerical quality indices in many applications.This paper discusses monitoring product surface in wafer testing of a semiconductor manufacturing process, since poor quality of surface affects wafer yield.Due to the spatial characteristics of wafer defects, a variable selection method is proposed using the fused LASSO algorithm to identify spatial clusters on the surface.Monte Carlo simulations have been conducted to compare the proposed method with industry benchmark and other competitive statistical process control (SPC) methods.A real example is presented to demonstrate the effectiveness of the proposed method.
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