Using Data Analysis Software to Model Semiconductor Yield and Define Optimal Process Space
semiconductor

Using Data Analysis Software to Model Semiconductor Yield and Define Optimal Process Space

Data analysis software is used extensively throughout all sectors of the semiconductor industry. These sectors include product, yield, and integration engineering; process and equipment engineering; quality and reliability engineering; design and device engineering; and assembly and test engineering. In this 60-minute Webinar, we will take on the role of a process integration engineer at a semiconductor fabrication company and learn how they can use data analysis software to quickly generate an analysis workflow. This workflow will reshape, join, and cleanup data from different data sources and assess variable importance, as well as generate an interactive yield dashboard and a predictive yield model. Through the workflow we also will define a process window to optimize yield.

Attendees will learn about:

  • Applying machine learning methods
  • Interactive visuals/dashboards
  • Predictive modeling and model simulation

An audience Q&A session will follow the technical presentation.

Speaker:

Mark Zwald, Senior Systems Engineer, JMP Statistical Discovery

Mark Zwald is a Senior Systems Engineer at JMP, where he supports strategic accounts and customer development in the western United States. He has nearly 20 years of experience in the semiconductor and consumer electronics industries and previously worked as a product engineer for ON Semiconductor, Intel, and Microsoft prior to joining JMP. Mark holds a bachelor’s and master’s degree in applied and engineering physics from Cornell University.

Moderator:

Amanda Hosey, Editor, SAE Media Group

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