A Review of Statistical Methods for Quality Improvement and Control in Nanotechnology

被引:29
|
作者
Lu, Jye-Chyi [1 ]
Jeng, Shuen-Lin [2 ]
Wang, Kaibo [3 ]
机构
[1] Georgia Inst Technol, Sch Ind & Syst Engn, Atlanta, GA 30332 USA
[2] Natl Cheng Kung Univ, Dept Stat, Tainan 701, Taiwan
[3] Tsinghua Univ, Dept Ind Engn, Beijing 100084, Peoples R China
基金
美国国家科学基金会; 中国国家自然科学基金;
关键词
Automatic Control; Experimental Design; Nanomanufacturing; Physical-Statistical Modeling; Statistical Quality Control; Stochastic Modeling; PROCESS ADJUSTMENT; SURFACE-ROUGHNESS; AUTOMATIC-CONTROL; FEEDBACK-CONTROL; STOCHASTIC PDE; TAGUCHI METHOD; ULTRA-THIN; DESIGN; OPTIMIZATION; FILM;
D O I
10.1080/00224065.2009.11917770
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Nanotechnology has received a considerable amount of attention from various fields and has become a multidisciplinary subject, where several research ventures have taken place in recent years. This field is expected to affect every sector of our economy and daily life in the near future. Besides advances in physics, chemistry, biology, and other science-based technologies, the use of statistical methods has also helped the rapid development of nanotechnology in terms of data collection, treatment-effect estimation, hypothesis testing, and quality control. This paper reviews some instances where statistical methods have been used in nanoscale applications. Topics include experimental design, uncertainty modeling, process optimization and monitoring, and areas for future research efforts.
引用
收藏
页码:148 / 164
页数:17
相关论文
共 50 条