<p>Improving the quality and yield of integrated circuit packaging processes is crucial for reducing scrap rates and component failures. Among all stages of the packaging chain, gold wire bonding is widely considered a critical process with a clearly defined role. According to the Taguchi loss function, insufficient gold wire bonding capability significantly degrades the performance of integrated circuit components, leading to premature failure. Due to the indispensable role of integrated circuit components in applications such as network communications, consumer electronics, and the automotive, industrial, aerospace, and defense sectors, any failure could disrupt operations, cause economic losses, and increase carbon emissions. This makes rapid decision-making essential and has led to a growing trend towards decision-making based on small sample sizes. Furthermore, the increasingly mature smart manufacturing environment and the continuous advancements in the Internet of Things as well as production data collection and analysis technologies have facilitated the accumulation of past professional data experience within the industry. This study thus proposes a confidence interval-based fuzzy evaluation method to establish a fuzzy evaluation model for the operational performance of integrated circuit components based on gold wire bonding process capability. Given that this method integrates previously accumulated professional data and experience and is based on confidence intervals, not only can the accuracy of decision-making be maintained, but the risk of misjudgment due to sampling errors even with a small sample size can also be reduced.</p>