Reliability Edge Newsletter

Quarter 1, 2001:  Volume 2, Issue 1

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Research

R&D Breakthroughs in Software
ReliaSoft has made some research and development advances that are being incorporated in new versions of ReliaSoft’s software products:

  • Generalized gamma distribution (MLE solution with confidence bounds) ~ Weibull++ 6

  • Likelihood ratio confidence bounds ~ Weibull++ 6

  • Accelerated life testing models with time-varying stresses ~ ALTA Pro

  • Confidence bounds for competing failure modes ~ Weibull++ 6

Research Publications
ReliaSoft’s representatives presented four papers and a tutorial at the 47th Annual International Symposium on Product Quality and Integrity, the Reliability and Maintainability Symposium (RAMS), held in Philadelphia, Pennsylvania, USA, January 22-25, 2001. The papers (available in *.pdf format on the Web) included:

"System Reliability Analysis: The Advantages of Using Analytical Methods to Analyze Non-Repairable Systems" in which ReliaSoft’s Adamantios Mettas and Marios Savva summarize the advantages of analytical methods over those of simulation for estimating the reliability of non-repairable systems.

"Determination and Interpretation of Activation Energy Using Accelerated-Test Data" in which ReliaSoft’s David Groebel and Adamantios Mettas collaborate with Dr. Feng-Bin Sun (Principal Reliability Engineer, Quantum Corporation) to show how calculating the activation energy of a component or system based upon accelerated life test data is tied to acceleration factors, confidence bounds and reliability predictions.

"Reliability Leadership" in which Dr. David Olwell, Director of ReliaSoft Professional Services, the consulting arm of ReliaSoft Corporation, presents hints on educating the boss about reliability issues and their impact on the bottom line.

"Warranty Calculations for Missiles with Only Current-Status Data, Using Bayesian Methods" in which Dr. David Olwell and Anthony A. Sorrell describe the risk assessment of extending the life of a class of missile, despite sparse failure data, using Bayesian methods.