Control of a semiconductor dry etch process using variation and correlation analyses

Statistical process control (SPC) is one of the traditional quality control methods that, if correctly applied, can be effective to improve and maintain quality and yield in any manufacturing facility. The purpose of this project is to demonstrate how to effectively apply SPC to a dry etch process (in this case plasma ashing), at Analog Devices, Inc., a company that runs large-scale fabrication sites in the Boston area. This thesis focuses on spatial and run-to-run variation across multiple measurement sites on a wafer and validates the assumptions of normality and correlation between sites within a wafer in order to justify and confirm the value of employing SPC theories to the plasma ashing process. By plotting control charts on past data, outlier data points are detected using Analog's current monitoring system. Further, irregularities in the process that would not have been detected using traditional x-bar Shewhart charts are detected by monitoring non-uniformity. Finally, cost analysis suggests that implementing SPC would be a modest investment relative to the potential savings.

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Mechanical Engineering.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2016

Author dc:creator

• Nilgianskul, Tan

Advisor dc:contributor.advisor

• Duane S. Boning.

• Mechanical Engineering.

Statement dc:rights

• MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/107025

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/107025