The most advanced and intuitive MTBF analysis software available for today’s reliability engineers
Relyence Reliability Prediction Software Overview
Why choose Relyence for your reliability prediction analysis software?
The Complete Package
Fully supporting the worldwide accepted standards for prediction analyses – MIL-HDBK-217, Telcordia, 217Plus, NSWC Mechanical, ANSI/VITA 51.1, and China’s GJB/z 299 – and adding features such as NPRD & EPRD support, dormancy, mission profiles, pi factor viewing, and failure rate adjustments based on lab test and field data, Relyence’s MTBF software is your complete prediction analysis package.
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Delve deeper into Reliability Prediction with our informative white papers
Spotlight on Reliability Prediction
Discover the unparalleled features that make Relyence the choice platform for MTBF software
The Advantages of Reliability Prediction Analysis
Key benefits of reliability prediction analyses
Reliability Prediction Software – What & Why
Answering the key questions about reliability prediction software tools
A Reliability Prediction is a way to analyze an electro-mechanical system to determine its predicted failure rate. Sometimes Reliability Prediction analysis is referred to as MTBF analysis. MTBF (Mean Time Between Failure or Mean Time Before Failure) and failure rate are related metrics in reliability engineering. Learn more about MTBF.
Reliability Predictions take into account all the components in your system along with design and environmental parameters known to affect reliability such as operating stresses, temperature, environment, and procurement quality level. A Reliability Prediction analysis uses underlying mathematical equations developed based on historical and known failure metrics to compute a predicted failure rate of your product.
One of the main advantages of reliability predictions is that they can be performed during the product design stage, enabling you to preview likely reliability metrics prior to manufacture and deployment. This enables you to design-in reliability, so you can be confident your product will achieve your reliability and quality goals when built.
In the product lifecycle, the cost of correcting a failure dramatically increases along every stage of a product’s life. In early design, design changes incur minimal cost: engineering time associated with the redesign. Design changes required later to correct defects incur huge costs – manufacturing line downtime, recalls, product replacement, etc. – not to mention the immeasurable negative costs to your reputation and corporate standing. Reliability Predictions are a fundamental and proven approach for early reliability assessment.
Reliability Predictions also provide a way to perform design comparison analyses, which allow you to quantifiably measure the reliability of various design alternatives. For example, you may have two proposed designs for a specific subsystem. Using Reliability Prediction MTBF analysis, you can view the predicted reliability profile of each design and make a decision based on clear metrics.
Lastly, Reliability Predictions may be performed to meet compliance requirements. In some situations, vendors may be contractually obligated to meet specific MTBF goals. Armed with MTBF assessments from Reliability Prediction analyses, your compliance requirements can be attained.
Check out our blog post for more about the benefits of MTBF analysis.
Although it is possible to perform Reliability Predictions by hand or with simple Excel spreadsheets, the most efficient way is to use a Reliability Prediction software package designed and built expressly for this purpose.
Reliability Prediction software should support the most commonly used and accepted standards, and the most recent editions of those standards. Widely used standards for Reliability Predictions include MIL-HDBK-217, Telcordia SR-332, 217Plus, and NSWC Mechanical.
Each standard varies and also has its own unique set of features to augment and improve MTBF analysis, such as adjustments for laboratory and field-based data. Reliability Prediction software should implement each standard fully. It’s even better if the Reliability Prediction package allows you to utilize these additional features across all standards for improved MTBF predictions – referred to as model extensibility.
Beyond the core capabilities defined in the standards, strong Reliability Prediction packages offer a wealth of capabilities for efficiency and automation such as:
- Built-in component libraries for easy look-up of device data and the ability to have your own internal component device database
- Part mapping for rapid and efficient data entry
- Built-in default data values and user-definable default values so MTBF analysis can be done before all design parameters are finalized
- Custom reports, graphs, and dashboard overviews
- Support for What-If? analysis and Mission Profiles
- Ability to import BOMs (Bill of Materials)
- Easy integration with other reliability tools
Want to learn more about MTBF?
Relyence Reliability Prediction is the standard in prediction analyses due to its combination of technical excellence and unparalleled customer service and support. Organizations around the globe rely on Relyence to deliver the most advanced and accurate prediction analyses, incorporating the latest technologies for maximum efficiency in today’s virtual and collaborative workplace.
Some examples of the excellence you can expect from Relyence:
- Support for an array of reliability prediction standards, as well as the ability to mix standards for the most effective analyses
- Built-in component libraries as well as our innovative and unique intelligent part mapping for device data
- A comprehensive list of capabilities for a superior and robust prediction package
- Integration with other analysis tools for a complete engineering analysis platform
- An unparalleled support team that is there to answer the call and provide rapid response
See how Relyence Reliability Prediction can meet your reliability prediction analysis needs. Start your no-hassle, free trial today!
Want to learn more?
Check out our blog for more information on reliability predictions, Relyence Reliability Prediction, and other reliability & quality topics.
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