Mathias Botzler, Peter Zeiler, and Bernd Bertsche, all of the Institute of Machine Components at the University of Stuttgart, Germany won the award for the best paper by an ASQ Reliability Division member at the 2014 Reliability and Maintainability Symposium.
Their paper, “Failure Prediction By Means Of Advanced Usage Data Analysis”, presents an innovative, 2-step procedure for analyzing observed field reliability data in order to improve maintenance procedures for capital goods. The first step is based on physical knowledge of the equipment and is used to condense the large amount of data that is typically collected from the electronic control units in such equipment to facilitate further analysis. The second step is applied to the pre-condensed data to incorporate unknown effects and degradation mechanisms into the analysis. The methods are then combined to yield a sharper image of the observed field reliability, increase the reliability knowledge of the product, and enable innovative and more economical maintenance policies.
