Browsing by Author "Tai, Yu Ting"

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Analytic Solution to Product Acceptance Determination for Gold Bumping Process With Multiple Manufacturing Lines
(2013-11-01)
Pearn, Wen Lea
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Tai, Yu Ting
;
Wu, Chia Huang
;
Chuang, Ching Ching
;
工業工程與管理學系
In recent years, gold bumping process has been applied extensively for the package technology of liquid crystal display driver integrated circuit, which is an essential component in portable devices. Because the increasing requirement of high-definition display devices, the gold bumping process has become more difficult and it is requested to be of high quality with very low fraction of defectives. Unfortunately, conventional methods for product acceptance determination no longer work because any sample of reasonable size probably contains no defective gold bump product items. In addition, in the globally competitive manufacturing environment, gold bumping processes involving multiple manufacturing lines are quite common in the Science-Based Industrial Park in Hsinchu, Taiwan, because of economic scale considerations. In this paper, we provide analytical solutions to gold bump product acceptance determination, which provide both manufacturers and customers to reserve their own rights by compromising on a rule for gold bumping process with multiple manufacturing lines. For the convenience of inplant applications, we tabulate the number of required inspection units, the critical acceptance values for various manufacturer's risks and consumer's risks, and various number of manufacturing lines. For illustration purpose, a real application in a gold bumping factory, which is located in the Science-Based Industrial Park in Hsinchu, Taiwan, is included.
Lower confidence bounds as precision measure for truncated processes
(2017)
Wu, Chia Huang
;
Pearn, Wen Lea
;
Tai, Yu Ting
;
Lin, Pi Chuan
;
工業工程與管理學系
Process capability index C-p has been the most popular one used in the manufacturing industry to provide numerical measures on process precision. For normally distributed processes with automatic fully inspections, the inspected processes follow truncated normal distributions. In this article, we provide the formulae of moments used for the Edgeworth approximation on the precision measurement C-p for truncated normally distributed processes. Based on the developed moments, lower confidence bounds with various sample sizes and confidence levels are provided and tabulated. Consequently, practitioners can use lower confidence bounds to determine whether their manufacturing processes are capable of preset precision requirements.