Case Study: SK Hynix achieves faster semiconductor R&D and greater manufacturing efficiency with JMP

Semiconductor giant SK Hynix creates efficiencies in technological development through machine learning

SK Hynix, one of the world’s largest semiconductor manufacturers, needed to build the know-how and data infrastructure to improve design of experiments (DOE) in R&D, with the goal of increasing automation, saving time, and boosting efficiency in a highly competitive industry. The company’s Data Innovations Team also needed a better way to visualize complex experiment data and communicate results across technical and non-technical teams.

JMP helped SK Hynix create machine learning and statistical workflows to streamline experimentation and standardize analytics across the organization. By using JMP for DOE, SK Hynix dramatically reduced required sample sizes, improved analysis time, and created stronger synergies between teams, expanding the impact of machine learning-based operations across the company.

SK Hynix

Yonghan Ju

Head of Data Innovations