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Tucson Section


IEEE Section Meeting


There is a meeting for the Reliability Society Chapter coming up. Please note the change from the typical location: 
University of Arizona Engineering building, room 214 
March 16 between 6pm and 9pm. 
Dinner will be served starting at 5:30pm. 
Room will be opened starting at 5pm. 
Park in the Second Street Garage. 
Directions to the 2nd Street Garage----- Speedway to Mountain. 
South on Mountain to 2nd Street. 
There is a stoplight there. 
Turn left. 
You will see the Garage. 
Even though it is Spring Break, you will still have to pay for parking. 
Directions to the Engineering building 
Once parked, leave the garage towards the buildings (south). 
You will see a TALL building. That is the Administration Building. 
Go west -past the Student Union. 
Then you will see the Engineering building. 
Bayesian Reliability Presentation 
Allan T. Mense, Ph.D., PE, CRE, Principal Fellow, Raytheon Missile Systems, Tucson, AZ 
This presentation will cover Bayesian reliability theory and Monte Carlo Markov Chain (MCMC) solution methods. In reliability analysis it makes a great deal of practical sense to use all the information available, old and/or new, objective or subjective, when making decisions under uncertainty. This is especially true when the consequences of the decisions can have a significant impact, financial or otherwise. Most of us make every day personal decisions this way, using an intuitive process based on our experience and subjective judgments. Mainstream statistical analysis, however, seeks objectivity by generally restricting the information used in an analysis to that obtained from a current set of clearly relevant data. Prior knowledge is not used except to suggest the choice of a particular population model to "fit" to the data, and this choice is later checked against the data for reasonableness. Lifetime or repair models using frequentist methods have one or more unknown parameters, e.g. l in an exponential failure model R(t) = exp[-lt].  The frequentist approach considers parameters as fixed but unknown constants to be estimated using sample data,( e.g. times to failure) taken randomly from the population of interest. The Bayesian approach treats these population model parameters as random, not fixed, quantities. Before looking at the current data, use is made of old information, or even subjective judgments, to construct a prior distribution model for these parameters. Current data (via Bayes’ formula) is used to revise the starting assessment, deriving what is called the posterior distribution model for the population model parameters. Parameter estimates, along with confidence intervals (known as credibility intervals), are calculated directly from the posterior distribution. Credibility intervals are legitimate probability statements about the unknown parameters, since these parameters now are considered random, not fixed.  The advantage in using Bayesian statistics is that it allows prior information (e.g., predictions, test results, engineering judgment) to be combined with more recent information, such as test or field data, in order to arrive at a prediction/assessment of reliability based upon a combination of all available information. 
Dr. Mense is a Principal Engineering Fellow at Raytheon Missile Systems, Tucson, Arizona. He is a principal advisor to the director of systems engineering responsible for technical reviews for all missile systems.  He is a co-developer and instructor for Raytheon-wide courses on Bayesian Reliability, Statistical Design Methods and Statistical Design of Experiments (DOEs).  Prior to joining Raytheon, Allan was the lead systems engineer for Motorola in satellite & spacecraft integration, and systems engineer for largest commercial satellite communications network undertaken in USA SATCOM (Iridium & Teledesic). He held the positions of Vice President for Research and Professor of Physics at Florida Institute of Technology. He operated as chief technology officer and business development / marketing director for entire university. Dr. Mense was member of a Science & Technology Committee in U.S. House of Representatives. He was a member U.S. Army Science Board and member of the National Academy of Engineering Study Boards. Dr. Mense is registered as a Professional Engineer (PE) in the State of Arizona and a Certified Reliability Engineer (CRE) with ASQ.

Have a interesting topic and know a good speaker, please contact us



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