Minjeong Cho | AI Transformation Engineer
SK Hynix
I am an AI transformation engineer with a background in semiconductor manufacturing.
I focus on data analytics, web-based engineering platforms, and building agentic AI systems that support data-driven and autonomous decision-making in fab operations.
Appearances:
Future of Memory and Storage - Day 2 @ 08:35
Autonomous Fab Journey: From AI-Assisted Decisions to Agentic Manufacturing
In semiconductor manufacturing, many day‑to‑day decisions follow formal rules, yet in practice they still rely heavily on individual engineer experience. Decisions such as interpreting marginal trends or tuning interacting parameters vary across engineers, leading to inconsistency and human error. Our goal is to reduce this variability by defining data‑driven, shared decision criteria, while also capturing how experienced engineers decide in real situations.To achieve this, we have been developing a stepwise roadmap toward an Autonomous Fab. We began with analytical models addressing pain points identified by field engineers, then introduced LLM‑based AI assistants using proprietary, domain‑specific fab databases with natural language access to process, equipment, and operations. Building on this foundation, we are now developing task‑oriented AI agents that combine LLMs, analytical models, and rule‑based logic to support judgment‑intensive tasks such as trouble lot handling and abnormal trend resolution. AI‑generated recommendations are reviewed by engineers, shifting their role toward validation and exception handling, with the long‑term goal of enabling a fully autonomous fab.
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