Roles of Dynamic Characteristics on Physical Behavior During Chemical Mechanical Planarization process

• Main Authors: Wu, Li-Hsin, 吳立信
• Other Authors: Cheng, Pi-Ying
• Format: Others
• Language: en_US
• Published: 1998
• Online Access: http://ndltd.ncl.edu.tw/handle/31660510264480946401

碩士 === 國立交通大學 === 機械工程研究所 === 86 === 　　CMP (Chemical mechanical polishing) is recognized to be of critical importance to high performance interconnect technology. In the CMP process, although conventional CMP technology can process characteristics such as removal rate, nonuniformity, degree of planarization, and surface defects, they still fail to meet the flatness to upgrade and yield a plannarized wafer with high global thickness uniformity due to the absence of instant dynamic process constraints involved. The conventional approach is oversimplified for planarization as well as removal rate to advance since it has ignored the configuration of a wafer in action. However, a novel parametric control algorithm is presented to meet the industrial specifications with high global thickness uniformity, The concern of the dynamic constraints nust be implemented efficiently to achieve an unprecedented degree of thin film smoothness. The simulation results are then compared to those with respect to the conventional technique. It is expected to be increased the uniformity and removal rate. The product characteristics of concern are the removal rate (corresponding to a controlled amount of oxide polished during the step) and the within-wafer uniformity of that removal rate across the wafer. This paper attempts to advance the state of the practice to CMP process control by applying a new algorithmic control technology. In this work, we outline the CMP process and the control scheme used for simulations. The basis idea behind the process is set into two parts. Firstly, system speed, and its kinematics are detected and optimized to a predicted extednd of non-uniformity. Secondly, wafer surface pressure is imaged on prescale films. And then wafer surface images in environments are developed and transferred into 3-D data patterns. This output helps understanding the distribution of pressure over a wafer and improving the conventional model based recipes.