Yield Enhancement in Wafer Manufacturing Through Applying Statistical Process Control Concepts

Although semiconductor fabrication has advanced significantly in recent years, manufacturing lines frequently encounter operational inefficiencies when processing highly specialized or non-standard substrates. These disruptions degrade overall line performance and ultimately reduce product yield. This issue is equally pronounced at the single-device level, where performance degradation and elevated defect rates necessitate substantial resource allocation for post-fabrication screening and inspection to prevent faulty components from reaching end users. The better practice is to try and discover, and consequently, eliminate the bad devices before they run through multiple processes, costing time and money towards a useless end. In some cases, the solution to overcome these difficulties becomes as costly as it involves modification of properties at the individual device level. This in turn saves the product quality, but still consumes resources to a point making the production process marginally profitable. A better solution to such problem is one that approaches the wafer as a whole and not at the device level. Given that these wafers typically accommodate roughly a thousand individual devices, adopting a global, wafer-level approach becomes highly advantageous. This paper addresses a real-world industrial challenge encountered during wafer fabrication when attempting to meet strict target specifications. This issue consistently arises in wafers processed via evaporated metal thin-film deposition. A prominent example of such components includes passive filters designed around Surface Acoustic Wave (SAW) principles. A solution that replaces the existing custom-made one is proposed. This solution eliminates approaching every device on the wafer individually and looks at the wafer as a whole. The proposed solution applies a statistical approach to the problem using the concepts of statistical process control. Implementing this solution yields substantial improvements, including a marked increase in product yield, significant cost reductions, and the successful integration and promotion of process automation.