Abstract Scope |
Photolithography, consuming the longest time and the highest cost among manufacturing processes, has developed to achieve maximum productivity over the past few decades. To maximize productivity, the usage time of the equipment is categorized through a time-based productivity model, which is based on big data comprised total 237 billion data in Samsung electronics for six months. These enormous data sets are designed to find causes of productivity degradation faster and more accurately than ever before. On the other hand, productivity improvements often lead to quality degradation. To prevent this trade-off, the overall equipment efficiency is designed to include the quality element of products. This paper could categorize productivity improvement into four sectors: continuity, synchronization, elimination, and reduction based on the time-based productivity model. Our study would pave the road to utilize a systematic approach to big data for the lithography process. |