Reliability HotWire

Reliability HotWire

Issue 131, January 2012

Tool Tips

*How can I use BlockSim 7 to figure out how to achieve a system reliability goal?

When developing a new product, an engineer often is given the reliability target and must then develop a design that will achieve the desired system reliability while performing all of the system's intended functions at a minimum cost. This involves a balancing act of determining how to allocate reliability to the components so the system will meet its reliability goal, while at the same time ensuring that the system meets all of the other associated performance specifications. BlockSim 7’s optimization calculations can help to determine the optimum scenario to increase the reliability of one or more individual components in order to achieve the system reliability goal that you specify.

To perform optimization calculations for the current RBD or fault tree, you must first decide which blocks will be included in the calculations. For each block that you want to include, select the Block to be used in optimized allocation check box on the Reliability Allocation page of the Block Properties window. In addition, enter the Maximum Achievable Reliability for the block and specify the feasibility of improvement (i.e., how difficult or costly it is to increase the reliability of the block). Feasibility may be specified by dragging the slider on the scale of Easy to Hard (relative to the difficulty/cost of improving other blocks in the system), or by a user-defined cost function.

Once you have specified the Reliability Allocation properties for each block that you want to include in the calculations, open the Analytical QCP. On the Optimization page, enter the following:

  • The Mission End Time is the time associated with the target reliability. For example, if you want to determine the optimum scenario for increasing component reliability in order to achieve system reliability of .98 at 100 days, you would enter 100 as the mission end time.

  • The Reliability Goal is the system reliability that you are trying to reach at the specified time. This number must be greater than 0 and less than 1. For example, if you want to determine the optimum scenario for increasing component reliability in order to achieve a system reliability of .98 at 100 days, you would enter .98 as the reliability goal.

  • The Iterations field allows you to specify the maximum number of iterations of the optimization algorithm that may be conducted in order to obtain a solution.

The results of the optimization calculations are displayed in the Results Panel, as shown next.

For each block considered in the optimization calculations, the following results are given:

  • Reliability(Mission End Time) is the current reliability for the component as calculated at the specified mission end time.

  • Goal(Mission End Time) is the reliability of the component that would be required in the optimum scenario to reach the specified system reliability goal.

  • N.E.P.U. (i.e., Number of Equivalent Parallel Units) is the number of identical blocks that you would have to place in a parallel configuration in order for the particular block to meet the specified reliability goal, in lieu of increasing the component’s inherent reliability.

For the system overall, the System Reliability row displays the calculated reliability and the reliability that could be expected if the optimum scenario were implemented.

For more information on optimization calculations, please refer to

*In Weibull++ 7, is there a way to perform a quick what-if analysis on a failure model without supplying data?

You can perform what-if analyses in Weibull++ 7 even when the only information you have is the distribution and its parameters. There are two methods available: analyze the distribution without using any data at all or generate a simulated data set that is distributed according to the model.

To analyze a distribution without using a data set, create a Weibull++ standard folio data sheet but do not enter any data. On the control panel, choose a distribution for the analysis and click the Calculate icon. The application will prompt you to enter the parameters. The following example shows the input window for a 2-parameter Weibull distribution.

Specify values for the parameters and click OK. You can use the plots and the QCP in the same way that you would for a calculated data set; however, calculations involving confidence bounds are not available.

To generate a simulated data set that is distributed according to a model, choose Tools > Generate Monte Carlo Data. Select a distribution, enter its parameters and enter the number of points to generate, as shown next.

Click Generate to create the simulated data set. You can then analyze the simulated data set then use the plots and QCP to obtain results. Confidence bounds calculations are available when you use this method.