Windchill Prediction
PTC Windchill Prediction analysis software
provides the basis for the reliability evaluation and analysis of systems by allowing you to to estimate component and system failure rate, MTBF and reliability early in the design process. Reliability prediction analysis techniques allow you to evaluate design feasibility and alternatives, identify problematic parts and verify progress in reliability engineering.
Increased Productivity. Easily import BOMs from, or export calculated results to, commonly used formats like Microsoft Excel, Microsoft Access, XML, and plain text files. The extensive parts libraries, including NPRD/EPRD, make prediction analyses immeasurably easier and more efficient by providing instant access to an extensive database of component information. Build company-specific parts and assemblies libraries to drastically reduce time calculating failure rates on components used most frequently.
Advanced Prediction Methodology. Windchill Prediction goes beyond the prediction standard methodology by adding an impressive number of functional enhancements to ensure all your prediction analysis needs are covered. Perform mission profile modeling, introduce reliability allocation methods, and model both active and dormant states. Additional features include derating analysis; user-defined parts, quality levels, and environments; and support for global data modifications.
Consulting Services. For clients that have an MTBF requirement, but don’t have the time or in-house expertise, Relex Italia offers MTBF Consulting Services.
Professional Outputs. Windchill Prediction is supplied with a range of industry standard reports and graphs. Easy-to-use Report and Graph Wizards provide complete user customization of outputs to fit your specific needs, without the need for IT experts. Once complete, reports and graphs can be printed or saved directly to Microsoft Word or Excel, and Adobe PDF.
Technical Highlights
Supported Standards
|
Advanced Methodology
|
Supported Calculations
|
Dynamic Data Links
|
Download the Reliability Prediction Data Sheet
