Censored Data Analysis of Experomental Design by Nonparametric Method
|關鍵字:||受限資料;迴歸分析;非參數方法;censored data;regression analysis;nonparametric method|
Experimental design is a critically important tool in the engineering world for improving the performance of a manufacturing process. It also has extensive applications in the development of new processes. Therefore, engineers usually improve the quality of products through the experiments. However, sometimes due to some controllable or uncontrollable causes (such as the damage of the instrument, out of electricity during the experiment, limitation of time and cost, etc.), only part of the experiment can be completed. In this case, the result of the experiment consists of the "complete" data and the "incomplete" data. Such incomplete data is called "censored data". For example, in the reliability testing for the I.C. products, we often obtain censored data from the experiment. Since the censored data contain less information than the complete data, it is more difficult to do the analysis. The objective of this research is to develop a cost-effective quality improvement technique for analyzing the censored data. Hopefully, through the correct analysis of the censored data, rather than redo the experiment to obtain the complete data, we may be able to obtain some important information about the optimization of the production and process. Since the procedure of nonparametric method is much easier to be understanded by the engineer, so the technique we plan to develop in this research is to analyze the mud-factor and multi-level censored data using the regression analysis and nonparametric method.
|Appears in Collections:||Thesis|