QUALITY CONTROL OF SEMICONDUCTOR PACKAGING BASED ON PRINCIPAL COMPONENTS ANALYSIS

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.

Identification of coastal water quality by multivariate statistical techniques in two typical bays of northern Zhejiang Province,East China Sea

The Hangzhou Bay（HZB） and Xiangshan Bay（XSB）, in northern Zhejiang Province and connect to the East China Sea（ECS） were considerably affected by the consequence of water quality degradation. In this study, we analyzed physical and biogeochemical properties of water quality via multivariate statistical techniques. Hierarchical cluster analysis（HCA） grouped HZB and XSB into two subareas of different pollution sources based on similar physical and biogeochemical properties. Principal component analysis（PCA） identified three latent pollution sources in HZB and XSB respectively and emphasized the importance of terrestrial inputs, coastal industries as well as natural processes in determining the water quality of the two bays. Therefore, proper measurement for the protection of aquatic ecoenvironment in HZB and XSB were of great urgency.

Research on uncertainty in measurement assisted alignment in aircraft assembly

Operations in assembling and joining large size aircraft components are changed to novel digital and flexible ways by digital measurement assisted alignment.Positions and orientations（P＆O）of aligned components are critical characters which assure geometrical positions and relationships of those components.Therefore,evaluating the P＆O of a component is considered necessary and critical for ensuring accuracy in aircraft assembly.Uncertainty of position and orientation（U-P＆O）,as a part of the evaluating result of P＆O,needs to be given for ensuring the integrity and credibility of the result;furthermore,U-P＆O is necessary for error tracing and quality evaluating of measurement assisted aircraft assembly.However,current research mainly focuses on the process integration of measurement with assembly,and usually ignores the uncertainty of measured result and its influence on quality evaluation.This paper focuses on the expression,analysis,and application of U-P＆O in measurement assisted alignment.The geometrical and algebraical connotations of U-P＆O are presented.Then,an analytical algorithm for evaluating the multi-dimensional U-P＆O is given,and the effect factors and characteristics of U-P＆O are discussed.Finally,U-P＆O is used to evaluate alignment in aircraft assembly for quality evaluating and improving.Cases are introduced with the methodology.