A Multivariate Exponentially Weighted Moving Average Monitoring Scheme Based on Optimal Estimating Functions for a Parametric Profile Model
博士 === 國立交通大學 === 統計學研究所 === 101 === In this paper, a statistical process control technique is developed for manufacturing processes, where the quality of the process can be better characterized and summarized by the relationship between the response variable and some relevant explanatory variables....
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| Format: | Others |
| Language: | en_US |
| Published: |
2013
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| Online Access: | http://ndltd.ncl.edu.tw/handle/52224135030514924410 |
| Summary: | 博士 === 國立交通大學 === 統計學研究所 === 101 === In this paper, a statistical process control technique is developed for manufacturing processes, where the quality of the process can be better characterized and summarized by the relationship between the response variable and some relevant explanatory variables. Firstly, a parametric profile model is described and then a multivariate exponentially weighted moving average monitoring scheme based on optimal estimating functions for a parametric profile model is proposed. Secondly, the proposed methodology is compared with Kim et al. (2003) and Zou et al. (2007) via a simulation study. Finally, some concluding remarks are given and possible future work is discussed.
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