Our goal at Fulton Findings is to further Weibull Engineering “WE” by simplifying Weibull plotting and Crow-AMSAA trending in the reliability, quality, maintainability, and safety areas with our clear, intuitive, touch-based software. Our “WE” training comes with a FULL software license for each participant to ensure their expert capability when the class is over.
“WE” uses statistical analysis for predicting life, quality, maintainability, risk, support cost, process reliability, and warranty. It includes Weibull, and all other useful distributions for modeling data variability. “WE” includes all facets of the journey; data collection, to analysis, to management decision.
Fulton Findings SuperSMITH® is for life to failure analysis, by taking extremely small samples, our software identifies failure modes and can predict future failures
CEO Wes Fulton created SuperSMITH® over 30 years ago and was partnered with the world renowned expert of Weibull analysis, Dr. Robert Abernethy. This partnership led Fulton Findings SuperSMITH® to be the one and only software program that is 100% compatible with the most widely used The New Weibull Handbook.
Fulton Findings operates world wide as companies all over the world buy software and take advantage of the classes and consulting that Fulton Findings provides. SuperSMITH® and accompanying software that Fulton Findings offers is the most in depth and specialized Weibull software in the industry.
Weibull, Data Plot, Graph, Statistical Software, Data Analysis, Reliability Software
Fulton Findings SuperSMITH® software is engineered for reliability and statistical analysis for predicting life, safety, survivability, risk, cost and warranty claims, substantiation and accelerated testing by using Weibull, log normal, Crow-AMSAA, probit and Kaplan-Meier models.
SuperSMITH® is the only software compatible with the industry leading the New Weibull handbook written by Dr. Robert Abernethy.
1) WE produces better models with smaller amounts of input data.
2) WE provides quantitative results with numbers instead of results based only on opinions.
3) WE plots illustrate the variability graphically making such results easier to interpret.
4) WE with Monte Carlo simulation yields the best goodness-of-fit indicator for graphical solution.
5) WE makes decisions easier for reliability-centered-maintenance (RCM) and condition-based-monitoring (CBM)
6) WE extensions like Abernethy Risk and Barringer Process Reliability help with decision-making.
7) WE for test planning gives the lowest-cost and/or the shortest-schedule plan for design substantiation.
8) WE encompasses accelerated testing and step-stress testing to minimize inception-to-market time
9) WE can add upper and lower bounds on nominal results using confidence estimates.
10) WE enables comparison between different options for significant difference, like between new and old designs.
11) WE includes other models and other methods like reliability growth trending for program management.