New and Enhanced Features in Version 7
The latest upgrade to RGA, Version 7, provides many new and enhanced features. This page presents a summary of these features.
Completely Updated and Enhanced User Interface
With the release of Version 7, the RGA interface has been completely re-designed and enhanced. The powerful and flexible interface allows you to keep all related analyses and information together in a single database file. Using the "Project Explorer" approach that is employed in many of ReliaSoft’s other applications (e.g. Weibull++, ALTA and BlockSim, among others), RGA provides an intuitive, hierarchical (tree) structure that allows you to view and manage multiple analyses, plots and attachments within a project.
Reliability Growth Program Planning and Analysis Across Multiple Test Phases
Although traditional reliability growth analysis models consider the data from a single phase of developmental testing, a reliability growth program often will be conducted across multiple phases. RGA now offers an array of new analysis and management tools based on the Crow Extended and Crow Extended - Continuous Evaluation models, which provide the appropriate calculations for reliability growth program planning and multi-phase data analysis.
Growth Planning Folio
The Growth Planning Folio allows you to define the amount of time planned for each phase in the testing program along with settings that describe the planned reliability growth management strategy. You can use this tool to make estimates about whether you will be able to achieve your MTBF goal with a given management strategy or to determine what strategy will be necessary to meet the established goal.
Multi-Phase Data Sheets
Multi-Phase Data Sheets make it possible for you to enter data from multiple phases of testing, using "Event Codes" to specify the end time for each phase, the specific test times when fixes were implemented and other details that can be considered by the model.
Multi-Phase Plot
You can use the Multi-Phase Plot to link the reliability growth program plan with your test data in order to track the progress and determine whether you will need to make adjustments in the remaining test phases in order to meet your MTBF goal.
Operational Mission Profiles
During a development program, it is common practice for systems to be subjected to operational testing in order to evaluate the performance of the system under conditions that represent actual use. It is also common for reliability fixes to be implemented in conjunction with this testing and to perform reliability growth analysis on the data obtained. However, when the system must be tested for a variety of different mission profiles, it can be a challenge to make sure that the testing is applied in a balanced manner that will yield data suitable for reliability growth analysis. RGA's new Mission Profile Folios can help you to:
- Create and manage an operational test plan that effectively balances all of the mission profiles that need to be tested.
- Track the expected vs. actual testing conducted for all mission profiles and validate that the testing has been conducted in a manner that will yield data sets that are appropriate for reliability growth analysis.
- If there are any significant variations from the test plan that could jeopardize the analysis results, you can use RGA to automatically group the data at specified "convergence points" so the growth model can be applied appropriately.
Design of Reliability Tests (DRT) for Repairable Systems
Design of Reliability Test (DRT) methods that are based on the parametric binomial, non-parametric binomial or exponential Chi-Squared methods are suitable for non-repairable items. However, when you want to design a reliability demonstration test for a repairable system that may fail and be restored multiple times during operation, another method is required.
With the release of Version 7, RGA now provides a DRT utility based on the NHPP model, which is suitable for repairable systems. This tool will help you to determine the amount of test time (or number of test units) that will be required to demonstrate a specified reliability goal (defined in terms of MTBF or failure intensity at a given time).
Monte Carlo Data Generation and SimuMatic®
With the release of Version 7, RGA now provides a Monte Carlo simulation utility that allows you to create data sets with values randomly generated based on the non-homogeneous Poisson process model. The SimuMatic® utility expands on this capability by automatically performing specified analyses on a large number of simulated data sets. For example, you may wish to use this tool to experiment with the impact of sample size or test time for reliability demonstration tests or to construct simulation-based confidence bounds.
