An improved measure of quality loss for notching processes. (28th July 2020)

• Record Type: Journal Article
• Authors: Wu, Chia Huang; Hsu, Ya Chen; Pearn, Wen Lea
• Is Part Of: Quality and reliability engineering international. Volume 37:Number 1(2021)
• Page Start: 108
• Page End: 122
• Publication Date: 2020-07-28
• Subjects: lower confidence bound -- notching processes -- parametric bootstrap method -- quality loss -- unbiased estimator; Reliability (Engineering) -- Periodicals; Quality control -- Periodicals; High technology -- Periodicals; 620.00452
• DOI: 10.1002/qre.2724
• Languages: English
• ISSNs: 0748-8017

Abstract

Abstract: 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 C pm 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 C pm and provide a step‐by‐step parametric bootstrap procedure for obtaining a composite lower confidence bound on C pm . 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.