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RENO: Probabilistic Event and Risk Analysis Visual Stochastic Event SimulatorSM
Flowchart and solve the most complex probabilistic problems.

EXAMPLES


Example R-1 - Snow Blower Reliability

Software Used: 
RENO


Problem Statement:

Reliability analysis on a certain snow blower yielded a Weibull life distribution with a beta of 2 and an eta of 400 hrs.

The snow blower will be deployed in a part of the country where the probability that it will snow on any given winter day is 1 in 10.

If it snows, then the snow depth is normally distributed with a mean of 6 inches and a standard deviation of 2.

Furthermore, the area of the driveways in that region is also normally distributed with a mean of 300 square feet and a standard deviation of 40.

If the snow blower clears 30 cubic feet an hour, what would the reliability of the blower be assuming 100 winter days?

RENO Solution:

Define a Probability called “SnowProbability” and a Constant called “SnowThreshold” to determine whether it will snow on a given day. If a random number uniformly distributed from 0 to 1 (generated by SnowProbability) is less than or equal to the fixed probability that it will snow on any given winter day (defined by SnowThreshold), this indicates that it snowed during the simulation.

Probability to be used with "Snow Threshold" to determine whether it snowed on a given day

Probability to be used with "SnowProbability" to determine whether it snowed on a given day

Define a Random Variable called “Snowfall_inches” to describe the depth of the snow.

Random Variable to describe the depth of the snow

Define a Random Variable called “Area_to_clean_ft2” to describe the area of the driveways.

Random Variable to describe the size of the driveways

Define an Equation Variable to describe the number of hours that the snow blower will be used based on the amount of snowfall and the area of the driveways.

Equation Variable to calculate the usage

Construct the flowchart as follows:

Flowchart to model the problem

Steps 1 and 2: Use a Block to generate a random number uniformly distributed from 0 to 1 (based on the Probability called “SnowProbability) and then use a Conditional Block to check whether it is less than or equal to the fixed probability of snow on any given winter day (based on the Constant called “SnowThreshold”). If true, this indicates that it snowed and the “Usage_Hours” are passed to the TRUE path. If false, this indicates that it did not snow and “0” is passed to the FALSE path.

Block to generate the random number Conditional Block to check the random number against the probability and determine if it snowed

Steps 3a and 3B: Use Flag constructs called “Snow” and “No Snow” to mark the TRUE and FALSE paths coming from the Conditional Block.

Step 4: Use a Summing Gate to accept the two incoming paths and perform a summation on the snow blower usage information that is passed to the construct. The result is one outgoing path.

Summing Gate to add the two incoming paths

Step 5: Use a Result Storage construct called “Usage” to store an average of the snow blower usage information that is passed to the construct.

Result Storage construct to store the average from all of the simulations

Step 6: Use a Block called “Reliability” to calculate the snow blower reliability. This equation uses RENO’s intrinsic function, WEIBULL_REL, which returns the Weibull reliability at a given time. The inputs to this intrinsic function are (Time, Beta, Eta, Gamma). The use of the reserved keyword IN indicates that the daily usage time from the previous “Usage” construct will be inserted into the equation for Time. Note: The list separator (,) given here is appropriate for the USA regional settings. If your regional settings differ, you must adjust the input accordingly. For example, under German regional settings, the input would be (Time; Beta; Eta; Gamma).

Block with equation to calculate the reliability

Step 7: Use another Result Storage construct called “Result” to store the last value.

After running 1,000 simulations (with a seed of 1 to provide repeatability), the results are displayed in the Simulation Results Explorer and in the flowchart, as shown next.

Flowchart with results displayed

The reliability is 98.5975%.

 

A RENO project with the solution for this example (called "Snow Blower.rnp") is shipped with the software and stored in the Examples\Reliability folder in the application directory (e.g. C:\Program Files\ReliaSoft\RENO\Examples\Reliability\Snow Blower.rnp).

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