Enhanced Virtual Metrology on Chemical Mechanical Planarization Process using an Integrated Model and Data-Driven Approach

Yuan Di,Xiaodong Jia,Jay Lee

doi:10.36001/ijphm.2017.v8i2.2641

Abstract

As an essential process in semiconductor manufacturing, Chemical Mechanical Planarization has been studied in recent decades and the material removal rate has been proved to be a critical performance indicator. Comparing with after-process metrology, virtual metrology shows advantages in production time saving and quick response to the process control. This paper presents an enhanced material removal rate prediction algorithm based on an integrated model and data-driven method. The proposed approach combines the physical mechanism and the influence of nearest neighbors, and extracts relevant features. The features are then input to construct multiple regression models, which are integrated to obtain the final prognosis. This method was evaluated by the PHM 2016 Data Challenge data sets and the result obtained the best mean squared error score among competitors.

Highlights

Chemical Mechanical Planarization (CMP) has been widely applied in the semiconductor industry as a crucial wafer polishing process (Steigerwald, Murarka & Gutmann, 2008)
In order to evaluate the performance of the CMP and employ the process control, the material removal rate (MRR) is derived as a performance indicator by measuring the layer thickness of the wafer after the process
This paper proposes an enhanced Virtual Metrology (VM) approach for the prediction of the MRR based on an integrated data-driven model

Summary

Introduction

Chemical Mechanical Planarization (CMP) has been widely applied in the semiconductor industry as a crucial wafer polishing process (Steigerwald, Murarka & Gutmann, 2008). In order to evaluate the performance of the CMP and employ the process control, the material removal rate (MRR) is derived as a performance indicator by measuring the layer thickness of the wafer after the process. Compared with the L2L control, the W2W control is obtaining more attentions since it can reduce the variability of the wafer processing and assure the product quality. The W2W control needs gauging every wafer, which will increase the production cycle time significantly. As an after-process measurement, the MRR calculation inevitably delays the control process and will degrade the APC performance

Methods

Results

Conclusion