Biostatistical Consulting Group: Statistical Process Monitoring Schemes for Discrete Silicon Wafer Data


Biostatistical Consulting Group: Statistical Process Monitoring Schemes for Discrete Silicon Wafer Data

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February 18, 2020 - 13:00 - 14:00
Team: Events, Training & News
Posted on January 31, 2020

CHIMb.ca
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Biostatistical Consulting Group: Statistical Process Monitoring Schemes for Discrete Silicon Wafer Data

Team: Events, Training & News

February 18, 2020 - 13:00 - 14:00

Description


Statistical Process Monitoring Schemes for Discrete Silicon Wafer Data

February 18, 2020
1:00 pm - 2:00 pm
A315, 3rd Floor, Chown Building, University of Manitoba

This research focuses on developing some advanced statistical monitoring schemes for efficient monitoring of two-dimensional silicon wafer data. Silicon wafers are commonly used materials in the semiconductor manufacturing industry. The data consists of the number of defects on the chips of newly produced wafers. It is observed that the data is non-negative, zero-inflated, highly skewed and has different peaks. A Zero-Inflated Mixture Poisson distribution perfectly fits the data. We consider the Maximization-Expectation algorithm to estimate the parameters of the distribution. Subsequently, we developed a Shewhart-type scheme to monitor changes in the average number of defects in wafers. A Distance-type scheme is also developed to monitor changes in the rate parameters of the distribution. The developed schemes are efficient in detecting an increase in the number of defects. The proposed schemes are illustrated with a simulated dataset and a real wafer dataset from a well-known electronics company.

Speaker:
Dr. Ridwan A. Sanusi
Post-Doctoral Fellow
Centre for Healthcare Innovation

Dr. Ridwan Sanusi has joined CHI as a post-doctoral fellow under supervision of Dr. Lix. Dr. Sanusi completed his PhD in 2019 at City University of Hong Kong in the Department of Systems Engineering and Engineering Management. Prior to this, he completed undergraduate and Master’s degrees in statistics. Dr. Sanusi brings expertise in the analysis of time series data. He is working with Dr. Lix on projects pertaining to statistical methods for longitudinal analysis of administrative health data and patient-reported outcomes data. 

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