Statistical Methods for Product Life Analysis and Accelerated Testing
October 20 & 21

Prof. William Q. Meeker, Iowa State University

Reliability improvement and reliability assurance processes in manufacturing industries require data-driven reliability information for making business, product-design, and engineering decisions. This will be a hands-on workshop where participants will use the JMP 11 software for analyzing reliability data and test planning. The course will focus on concepts, examples, models, data analysis, and interpretation. Examples and exercises will include examples using product field (maintenance or warranty) data, accelerated life tests, and accelerated degradation tests. After completing this course, participants will be able to recognize and properly deal with different kinds of reliability data and properly interpret important reliability metrics. Topics will include the use of probability plots to identify appropriate distributional models (e.g. Weibull and lognormal distributions), estimating important quantities like distribution quantiles and failure probabilities, the analysis of data with multiple failure modes, the analysis of both destructive and repeated measures degradation data, and the analysis of recurrence data from a fleet of systems or a reliability growth program.

Course Logistics:
Dates: October 20 & 21
Times: 9:00 AM to 5:00 PM
Location: BLS Conference & Training Center
Room: 7 & 8

Course Materials:


Book: "Statistical Methods for Reliability Data" by William Q. Meeker and Luis A. Escobar. John Wilely & Sons, 1998.
The book is provided at no cost to tutorial participants, courtesy of SAS JMP.

Handouts: Handouts will be  provided.

Laptop: Bring your own laptop for hands-on practice  of concepts. Please pre-install JMP.

Data: Course datas sets through the link: http://www.public.iastate.edu/~wqmeeker/stat533stuff/CourseReliabilityDataSets.zip

Software: JMP 30-day free trial copy through the link: http://www.jmp.com/software/try-jmp.shtml?ref=nav.
Data: Data for course exercises can be accessed at http://www.public.iastate.edu/~wqmeeker/stat533stuff/CourseReliabilityDataSets.zip

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