5 critical quality characteristics must be controlled in the surface mount and wire-bond process in semiconductor packaging. And these characteristics are correlated with each other. So the principal components analy...5 critical quality characteristics must be controlled in the surface mount and wire-bond process in semiconductor packaging. And these characteristics are correlated with each other. So the principal components analysis(PCA) is used in the analysis of the sample data firstly. And then the process is controlled with hotelling T^2 control chart for the first several principal components which contain sufficient information. Furthermore, a software tool is developed for this kind of problems. And with sample data from a surface mounting device(SMD) process, it is demonstrated that the T^2 control chart with PCA gets the same conclusion as without PCA, but the problem is transformed from high-dimensional one to a lower dimensional one, i.e., from 5 to 2 in this demonstration.展开更多
Karst depressions are common negative topographic landforms formed by the intense dissolution of soluble rocks and are widely developed in Guizhou province.In this work,an inventory of karst depressions in Guizhou was...Karst depressions are common negative topographic landforms formed by the intense dissolution of soluble rocks and are widely developed in Guizhou province.In this work,an inventory of karst depressions in Guizhou was established,and a total of approximately 256,400 karst depressions were extracted and found to be spatially clustered based on multidistance spatial cluster analysis with Ripley’s K function.The kernel density(KD)can transform the position data of the depressions into a smooth trend surface,and five different depression concentration areas were established based on the KD values.The results indicated that the karst depressions are clustered and developed in the south and west of Guizhou,while some areas in the southeast,east and north have poorly developed or no clustering.Additionally,the random forest(RF)model was used to rank the importance of factors affecting the distribution of karst depressions,and the results showed that the influence of lithology on the spatial distribution of karst depressions is absolutely dominant,followed by that of fault tectonics and hydrological conditions.The research results will contribute to the resource investigation of karst depressions and provide theoretical support for resource evaluation and sustainable utilization.展开更多
基金This project is supported by National Natural Science Foundation of China (No.70372062)Hi-Tech Program of Tianjin city,China (No.04310881R).
文摘5 critical quality characteristics must be controlled in the surface mount and wire-bond process in semiconductor packaging. And these characteristics are correlated with each other. So the principal components analysis(PCA) is used in the analysis of the sample data firstly. And then the process is controlled with hotelling T^2 control chart for the first several principal components which contain sufficient information. Furthermore, a software tool is developed for this kind of problems. And with sample data from a surface mounting device(SMD) process, it is demonstrated that the T^2 control chart with PCA gets the same conclusion as without PCA, but the problem is transformed from high-dimensional one to a lower dimensional one, i.e., from 5 to 2 in this demonstration.
基金The Science and Technology Foundation of Guizhou Province(2022-212),[2020]1Z052National Natural Science Foundation of China,No.42167025。
文摘Karst depressions are common negative topographic landforms formed by the intense dissolution of soluble rocks and are widely developed in Guizhou province.In this work,an inventory of karst depressions in Guizhou was established,and a total of approximately 256,400 karst depressions were extracted and found to be spatially clustered based on multidistance spatial cluster analysis with Ripley’s K function.The kernel density(KD)can transform the position data of the depressions into a smooth trend surface,and five different depression concentration areas were established based on the KD values.The results indicated that the karst depressions are clustered and developed in the south and west of Guizhou,while some areas in the southeast,east and north have poorly developed or no clustering.Additionally,the random forest(RF)model was used to rank the importance of factors affecting the distribution of karst depressions,and the results showed that the influence of lithology on the spatial distribution of karst depressions is absolutely dominant,followed by that of fault tectonics and hydrological conditions.The research results will contribute to the resource investigation of karst depressions and provide theoretical support for resource evaluation and sustainable utilization.