Analysis of Quality Improvement Effects in Process Control of Semiconductor Manufacturing Using Bayesian Networks

As demand for semiconductors continues to grow, there is an increasing need for higher speed and smaller size, along with enhanced functional requirements. The semiconductor manufacturing process consists of two main stages: the front-end process, in which circuits are formed on silicon wafers, and the back-end process, where semiconductors are cut from the wafers, fixed in designated positions, encapsulated, and assembled. This process involves hundreds of steps, and many of these can become bottlenecks due to factors such as high equipment utilization and unexpected equipment failures, leading to production delays. Many of these delay factors significantly impact product yield.