A recognized leader in Fault Tree Analysis

Fault Tree Analysis (FTA) is a top down, deductive analysis in which an undesired top-level event of a system is analyzed using Boolean logic to combine a series of lower-level events. Top-level undesired events and their severity classification are often previously determined in the Functional Hazard Analysis.

Fault Tree Analysis looks for various ways that individual components, or groups of components, would have to fail to produce undesirable events. Analysis results for each event are presented in a tree-like diagram using logic symbols to show how dependencies among components contribute to the undesirable event at the top level. In this way, Fault Tree Analysis provides valuable troubleshooting information. The diagram shows failure probabilities at each level, from components to the undesirable event. Our team will work with you to tailor an analysis to your needs and provide results that are most useful to you. Our experience can be applied to make any product safer, more dependable and more successful.

Developing software tools that compare FMEAs and corresponding FTAs

FTA and FMEA are usually performed by different analysts to assure independence of assessments and conclusions. The independent determinations must of course be consistent in both kinds of analyses, but consistency checking is difficult because completed analyses may run well over a thousand pages. To address this challenge, we have developed a software tool that compares FTAs and corresponding FMEAs.

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Cross-Checking Results of FMEA and FTA

What’s Inside: Results of Failure Modes and Effects Analysis (FMEA) and Fault Tree Analysis (FTA) of a system are often at odds because the two kinds of analysis are usually performed by different people using different approaches, and also because the analyses have different ground rules.  However, consistency of results can be significantly improved with certain techniques that cross check these results and identify discrepancies. These techniques can be partially automated to significantly and efficiently improve analysis quality, accuracy, and thoroughness.