Reliability Analysis with JMP®
The reliability of your product strongly influences business success – whether you’re making semiconductors, light bulbs, automobiles, shoes, medical devices or jet engines. Reliability analysis can help ensure that a product functions as intended throughout its life, guaranteeing happy customers who provide repeat business as well as referrals. Dependable products also reduce warranty costs, which can otherwise quickly eat away at your profit margins.
In contrast, product failure, or “field catastrophe,” diminishes consumer trust, tarnishes your brand and reputation, and reduces the likelihood that customers will return. When this happens, failure analysis is a way to determine what went wrong and how to fix the issue.
Life data analysis, or Weibull analysis, can help you prevent failure and improve warranty performance – two of the most important reasons for using reliability analysis to fully understand your products.
JMP sets itself apart from other reliability analysis software by integrating robust statistical analysis with dynamic data visualization to let you immediately spot trends and outliers in huge data sets. Its reliability analysis techniques help you pinpoint defects in materials or processes, finding design vulnerabilities and then determining how to correct them.
For instance, JMP offers the Reliability Growth platform so that you can model system reliability as improvements are incorporated into the design to increase mean time between failures (MTBF). The Reliability Forecast platform lets you analyze warranty return data to create reserve forecasts so that you will be certain to have enough capital budgeted to meet the costs of your warranty requirements.
Do you need to determine the best distribution to use for making accurate reliability lifetime predictions on your products and components? Let JMP automatically evaluate a large range of reliability distributions to find the best fit. If you prefer, use nonparametric procedures, or manually select and compare parametric distributions. JMP supports all methods in one easy-to-use Life Distribution fitting platform.The dynamic Profilers in JMP enable you to interactively determine lifetime estimates and extrapolate to future time periods.
When you have multiple independent failure modes identified in your data, you can use the Life Distribution competing cause option to analyze each cause separately. You can omit causes interactively and assess potential improvement in product quality. This powerful option lets you assign specific fitted distributions to each failure mode.
The JMP Fit Life by X platform lets you model the relationship between the event and the factor of interest, using various transformations, including Arrhenius, voltage, linear, log, logit, location, and location and scale.
The Degradation platform in JMP lets you analyze product deterioration data over time to help predict product quality and warranty risk. JMP enables you to analyze data resulting from both nondestructive (repeated measures or stability analysis) and destructive testing.Use the JMP Degradation platform to make performance predictions before products or components become ineffective (soft failures) or eventually become a hard failure.
The Reliability Growth platform lets you model the reliability of a single repairable system over time as improvements are incorporated into the design. This platform fits Crow-AMSAA models and also features a useful change point detection fitting procedure that automatically determines when phases of the reliability model have changed.
- Selected JMP capabilities in the area of Reliability
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