Explore our collection of peer-reviewed research articles
Showing 6 articles
Zhang, L., Rodriguez, M., & Kim, S.
This study presents a new methodology for multivariate statistical process control that leverages sigma-scaled metrics to improve detection sensitivity...
Anderson, P., Lee, J., & Thompson, R.
We investigate robust estimation methods applicable to quality engineering scenarios where traditional normality assumptions fail...
Patel, A., Chen, W., & O'Brien, K.
This paper explores the integration of machine learning algorithms within the traditional Six Sigma DMAIC framework to enhance predictive capabilities...
Williams, E., Kumar, R., & Santos, M.
We develop a comprehensive Bayesian framework for addressing quality control challenges in high-dimensional settings, with applications to modern manufacturing...
Nakamura, H., Smith, D., & Garcia, L.
This research investigates the application of deep learning techniques for automated anomaly detection within Six Sigma quality improvement initiatives...
Mueller, T., Johnson, A., & Park, Y.
A comprehensive review of statistical process monitoring techniques adapted for Industry 4.0 environments, including IoT integration and real-time analytics...
