Nowadays, electronic products are progressively becoming thinner, lighter, and more convenient for people to use. Printed circuit boards, and especially integrated circuit (IC) substrates, are among the essential component of these products. The IC substrate not only protects circuits, fixes lines, and conducts heat, but is also the critical component that provides signal connectivity between the chip, the printed circuit boards, and other crucial parts during the packaging process. The process capability index Cpm is commonly used to assess the product quality loss for decision making in modern semiconductor packaging manufacturing. For high‐definition products, packaging processes often have very strict quality requirements and thus the quality inspection procedure is time‐consuming and complicated. Therefore, because of the limitation of manpower and capacity of the inspection instruments, the collected sample for quality assessment may be with small to moderate sample sizes. In this paper, we introduce an unbiased estimator for Cpm and provide a step‐by‐step parametric bootstrap procedure for obtaining a composite lower confidence bound on Cpm. To compare with the approaches discussed in the literature, numerical simulations are conducted under various process parameter settings. The results show that for small to moderate sample sizes, the proposed method applying the unbiased estimator has more accurate coverage rates than the existing methods. At the end of this paper, an application of quality loss assessment in notching processes is demonstrated.
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 highdefinition 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.
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