Improve the NAND IC Sorting method via K-means and principal component analysis.

• Main Authors: Wang, 王雲輝
• Other Authors: 葉英傑
• Format: Others
• Language: zh-TW
• Published: 2019
• Online Access: http://ndltd.ncl.edu.tw/handle/843e3n

碩士 === 國立中央大學 === 工業管理研究所 === 107 === Since the memory products have been closely related to people lives, whether it is a mobile, computer and internet service provider, the storage device behind it has been update from hard disk drive (HDD) to solid state drive(SSD), the key point is the NAND by the this research. Therefore, in the memory product market, how to launch products in the fastest time and quality is good, this is already an important core competitiveness of each company. This study will use the K-means to group the NAND, classify the ICs with the same characteristics, so that product firmware developers can focus on the NAND and understand the characteristics of the group NAND with appropriate firmware algorithms to handler the process problem and other lot or grade. The experimental results show that the method of this study has the same characteristics in the same type and different batch of NAND, this can also be provided to the R&D and quality department for reference the product and material quality.