题目：Engineering-Knowledge-Driven Statistical Modeling for Spatial Data
时间：2015.4.14（星期二）上午10:00
主讲人：王凯波 副教授（清华大学工业工程系）
地点：主楼216
主讲人介绍：
    王凯波博士是清华大学工业工程系的副教授。他在香港科技大学获得工业工程与工程管理学博士学位。王凯波的研究主要关注复杂系统的质量建模、监视与控制。他是多个自然科学基金与企业资助科研项目的负责人，在质量控制领域SCI索引的国际期刊发表了30余篇论文，其中包括Journal of Quality Technology, IIE Transactions, IEEE Transactions of Automation Science and Engineering, Quality and Reliability Engineering International等。
内容介绍：
    In certain complex manufacturing systems, the quality of a product is adequately characterized by a high-dimensional data map rather than by single or multiple variables. Such data maps also preserve unique spatial structures. Therefore, variation pattern analysis and statistical modeling based on the data map become very important for enhanced process understanding and quality improvement.
    Using a real wafer example from semiconductor manufacturing and a carbon nano tube example from nano-manufacturing, we demonstrate how statistical models can be developed by incorporating engineering knowledge. In the wafer example, a three-stage hierarchical model is proposed. The wafer surface variation is decomposed into the macro- and micro-scale variations, which are modeled as a cubic curve and a first-order intrinsic Gaussian Markov random field, respectively. In the carbon nano tube example, a piece-wise polynomial model with spatial auto-regressive disturbance is developed. These examples show that engineering knowledge driven statistical modeling can play an important role in quality control of complex systems, and is also a promising area for statistical research.

（主办：管理工程系）