ReliaSoft RGA: Reliability Growth Analysis

ReliaSoft’s RGA is an application-oriented software with all of the major reliability growth models, plus advanced analysis methods that are not available anywhere else. Applications include the ability to:

• Quantify reliability growth achieved with each successive design prototype.
• Determine the feasibility of achieving reliability goals with a given test/fix strategy.
• Calculate optimum overhaul times and other results for fielded repairable systems without the detailed data sets that would normally be required for repairable system analysis.

RGA includes full support for traditional reliability growth analysis using the applicable models — Crow-AMSAA (NHPP), Duane, Gompertz, Modified Gompertz, Lloyd-Lipow or Logistic — for a variety of developmental data types — time-to-failure, discrete (success/failure) and reliability data. In addition, the software provides exclusive support for innovative approaches that facilitate reliability growth projections, reliability growth program planning and multi-phase reliability growth analysis.

RGA helps to create operational test plans that effectively balance all of the mission profiles that need to be tested to make sure the testing yields data appropriate for reliability growth analysis. The software also provides opportunities for fielded repairable system analysis, including a Design of Reliability Test (DRT) utility and a method for analyzing the system’s reliability behavior over time in order to calculate optimum overhaul times and other metrics of interest.

RGA supports all of the traditional reliability growth analysis models:

• Crow-AMSAA (NHPP)
• Duane
• Standard and Modified Gompertz
• Lloyd-Lipow
• Logistic

The software provides options for time-to-failure (continuous), discrete (success/failure) and reliability data from a variety of types of developmental reliability growth tests. The available model(s) depend on the type of data.

Available only in RGA, the software supports several innovative approaches that expand upon traditional reliability growth methods in ways that better represent real-world testing practices and practical applications.

• The Crow Extended model allows you to classify failure modes based on whether and when they will be fixed. This analysis allows you to make reliability growth projections and evaluate the reliability growth management strategy.
• The Growth Planning Folio helps you to create a multi-phase reliability growth testing plan. In addition, you can use the Crow Extended – Continuous Evaluation model to analyze data from multiple test phases and create a Multi-Phase Plot to compare your test results against the plan. This analysis will help to determine if it is necessary to make adjustments in subsequent test phases in order to meet your reliability goals.
• The Mission Profile Folio helps you to create a balanced operational test plan and track the actual testing against the plan to make sure the data will be suitable for reliability growth analysis.

RGA also provides opportunities for fielded repairable system analysis. This includes a new Design of Reliability Tests (DRT) utility for repairable systems (based on the non-homogeneous Poisson process) and data sheets that have been specially designed for the analysis of fielded system data. Depending on the characteristics of your data set, you may be able to:

• Analyze the failure times for fielded repairable systems in order to understand the reliability over time and calculate metrics of interest (such as optimum overhaul time or expected number of failures) without the detailed data sets that would normally be required.
• Evaluate the reliability improvement that you can expect from rolling out fixes for a fleet of units operating in the field.
• Use grouped (interval) data analysis to evaluate fleet warranty data in order to estimate future returns.

• Weibull++
• XFRACAS