ASQ RRD Series: Introduction to Fractional Failure and Its Application in Reliability Engineering & Risk Assessment
https://attendee.gotowebinar.com/register/7715189933900311307
Thu, Feb 13, 2020 12:00 PM – 1:00 PM EST
Presenter: Feng-Bin Sun – Senior Staff of Reliability Engineering, Tesla
The purpose of this presentation is to use numerical examples to demonstrate the data analysis for various fractional failure scenarios with the most popular commercial software in the market (such as Weibull++, JMP, and Minitab), including:
- data collection,
- failure classification,
- fractional failure determination,
- data entry format,
- life distribution parameter estimation,
- reliability quantification, and field risk prediction.
Dr. Feng-Bin (Frank) Sun is currently a Senior Staff Manager of Reliability Engineering and Technical Lead of Manufacturing Reliability at Tesla Inc. with over 30 years of industry and academia experience. Prior to joining Tesla, he worked at HGST, a Western Digital Company, as a Senior Technologist of Reliability Engineering from 2010 to 2015, at Western Digital Corporation as a Technical Team Leader from 2003 to 2010, and at Maxtor-Quantum Corporation as a Senior Staff Reliability Engineer from 1997 to 2003. He has published two books, both by Prentice Hall, and more than 50 papers in various areas of reliability, maintainability and quality engineering. He received his Ph.D. in Reliability from University of Arizona. Dr. Sun served in the editorial board as an Associate Editor for the IEEE Transactions on Reliability from 1999 to 2003 and from 2016 to present, Program Chair of ISSAT International Conference on Reliability and Quality in Design since 2014, and a committee member and session moderator of numerous international conference on reliability. He is a member of ASQ and the President for Society of Reliability Engineers Silicon (SRE) Valley Chapter. He is also the program manager in charge of ASQ Reliability Webinar Mandarin Series. Dr. Sun received the RAMS 2013 A.O. Plait Best Tutorial Award.
