FlexFit
Designed to improve every step of statistical analysis
FlexFit brings together data preparation, outlier detection, clustering, and intelligent distribution fitting in a single FlexSim module. From qualifying historical data to identifying the most representative statistical distributions, every step is designed to improve analytical accuracy, increase confidence in the results, and build more reliable simulation models.
Advanced data qualification
Prepare, organize, and qualify historical data through descriptive statistics, automated outlier detection, clustering, and standardized datasets before distribution fitting.
Intelligent distribution fitting
Automatically evaluate more than twenty statistical distributions, compare them using recognized statistical criteria, and identify the distribution that best represents your data.
Flexible analytical outputs
Customize analysis parameters, statistical criteria, and output formats to generate reports and analytical results tailored to your project's specific requirements.
EXPERIENCE THE FUTURE
A stronger statistical foundation for every FlexSim project.
Overcome the challenges behind reliable statistical modeling
- Improve statistical workflows in FlexSim
- Qualify historical data
- Detect outliers and failure patterns
- Generate representative statistical distributions
- Increase confidence in statistical inputs
Built for statistical accuracy at every stage
Technical differentiators for advanced statistical analysis:
- Native FlexSim integration
- Advanced curve fitting
- 20+ statistical distributions
- Goodness-of-fit testing
- AIC/BIC model ranking
- Descriptive statistics
- Automated outlier detection
- Failure mode clustering
- TBF & TTR processing
- Configurable workflows
- Custom reports & outputs
- Data preprocessing
Faq
Frequently asked questions and relevant information
Learn more about FlexFit, its statistical capabilities, FlexSim integration, supported analytical methods, and how the module helps generate more representative statistical distributions for industrial projects.
FlexFit prepares and qualifies historical data before statistical curve generation. It automatically detects outliers, identifies different failure behaviors, evaluates more than 20 statistical distributions, and selects the distribution that best represents the observed data using recognized statistical criteria.
Yes. FlexFit is designed as an integrated module for FlexSim, allowing users to perform advanced statistical processing and generate representative statistical inputs within the same simulation environment.
FlexFit can process historical operational and maintenance datasets, including TBF (Time Between Failures) and TTR (Time To Repair) data, supporting data preparation, statistical qualification, and automated distribution fitting for simulation and reliability studies.
Yes. Users can configure statistical parameters, analysis criteria, processing workflows, and output formats to match specific project requirements and organizational standards.
FlexFit automatically evaluates more than 20 statistical distributions and compares them using recognized goodness-of-fit criteria, including AIC and BIC rankings, to identify the most representative model for each dataset.
The module automatically detects statistical outliers and applies clustering techniques to separate different failure modes before curve fitting, helping generate statistical distributions that better represent real asset behavior.
Strengthen the statistical foundation of your FlexSim projects.
Discover how FlexFit combines advanced statistical analysis, intelligent data qualification, and automated curve fitting to generate representative statistical distributions and improve the quality of your FlexSim models.