Virtual metrology and feedback control for semiconductor manufacturing processes using recursive partial least squares

Abstract

Virtual metrology (VM) is the prediction of metrology variables (either measurable or non-measurable) using process state and product information. In the past few years VM has been proposed as a method to augment existing metrology and has the potential to be used in control schemes for improved process control in terms of both accuracy and speed. In this paper, we propose a VM based approach for process control of semiconductor manufacturing processes on a wafer-to-wafer (W2W) basis. VM is realized by utilizing the pre-process metrology data and more importantly the process data from the underlying tools that is generally collected in real-time for fault detection (FD) purposes. The approach is developed for a multi-input multi-output (MIMO) process that may experience metrology delays, consistent process drifts, and sudden shifts in process drifts. The partial least squares (PLS) modeling technique is applied in a novel way to derive a linear regression model for the underlying process, suitable for VM purposes. A recursive moving-window approach is developed to update the VM module whenever metrology data is available. The VM data is then utilized to develop a W2W process control capability using a common run-to-run control technique. The proposed approach is applied to a simulated MIMO process and the results show considerable improvement in wafer quality as compared to other control solutions that only use lot-to-lot metrology information.