Applying Six Sigma Methodology to Improve the Impedance Control Process of Touch-Sensing Glass

In recent years, the touch panel industry has experienced rapid growth. With technological maturation and progressive cost reduction, touch technology has been widely adopted in human–machine interfaces. Currently, touch panels are predominantly employed in smartphones and tablet devices, and the industry is increasingly pursuing thinner, lighter designs, driving the development of diverse touch technologies, including one-glass solution (OGS), on-cell, and in-cell architectures. To enhance competitive advantage within the touch panel industry, it is essential to improve production efficiency and elevate product quality; consequently, yield has become a critical metric for evaluating industrial competitiveness. This study adopts the electrical test yield of Touch-on-Lens (TOL) touch-sensing glass as the primary performance indicator. A Six Sigma DMAIC (Define, Measure, Analyze, Improve, Control) framework is applied to systematically address impedance-related quality defects occurring during manufacturing. First, key quality characteristics (KQCs) of the TOL touch-sensing glass process are rigorously defined. Subsequently, measurement system analysis (MSA) and process capability assessment are conducted. Next, the Taguchi method is employed to identify the most influential process factors affecting electrical test yield. Finally, response surface methodology (RSM) is utilized to determine the optimal combination of process parameter settings that maximize electrical test yield. Results from the empirical case study demonstrate that the electrical test yield improved significantly—from 90.2% to 93.6%. This outcome validates that the integrated application of the Six Sigma DMAIC methodology, combined with the Taguchi method and RSM, effectively enhances the electrical test yield of TOL sensing glass. The proposed approach offers a robust, data-driven improvement framework applicable to touch panel manufacturers seeking to optimize sensing-glass fabrication processes—thereby supporting broader industry efforts to improve product quality and reduce manufacturing costs.