Calculating Probability of Valve Failure in Q5: Exponential Distribution Model

In summary, the probability of a loss of flow from the manifold in the period (0,3) years is 0.08643, calculated by using an exponential distribution function with specified lambda values for the valves and time period of 3 years.
  • #1
abba02
11
0
[SOLVED] probability of failure

The performance of the valves in Q5 has been assessed in more detail under conditions

closer to those experienced in-service and the distribution functions of the random time

to failure have been quantified. The useful life period, prior to wear-out, occurs from

installtion to 5years. During this period, all of the distribution functions are modeled

using an exponential distribution function of the form:

FT (t) = 1 − exp[−_λit] where i=1,2,3,4,5

If _λ1 = λ_2 = _λ3 = 0.05; λ_4 = 0.267; λ_5 = 0.189 (all in years−1), calculate the probability

of a loss of flow from the manifold sometime in the period (0,3)years.

ANSWER[P[F]=0.08643]

ATTEMPT
Have tried to substitute .05 for lambada and 3 for t in the given equation but my answer is still very different from the given answer of 0.08643
 
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  • #2
The attempt at a solution:

V1,V2 AND V3 ARE IN SERIES AND SS1 ARE IN PARALLEL TO V4 AND V5

(PV1 OR PV2 OR PV3) AND PV4 AND PV5

FT (t) = 1 − exp[−_λit] where i=1,2,3,4,5

If _λ1 = λ_2 = _λ3 = 0.05; λ_4 = 0.267; λ_5 = 0.189 (all in years−1),

For PSS FT (t) =1- exp [-λ1+λ2+λ3*3] where t=3 = .36237

For PV4, FT (t) =1- exp [-λ4*3]=.55112

For PV5,FT (t) =1- exp [-λ5*3]= .43278

Therefore the probability of loss of flow from the manifold at time 3 years is

PSS1 AND PV4 AND PV5= .36237*.55112*.43278= .08643
 

What is the "Probability of Failure"?

The Probability of Failure is a measure of the likelihood that a particular event or system will fail or not meet its intended purpose. It is usually expressed as a percentage or decimal value between 0 and 1, with 0 indicating no chance of failure and 1 indicating certain failure.

How is the "Probability of Failure" calculated?

The calculation of Probability of Failure depends on the specific situation and the available data. In general, it involves analyzing the potential failure modes, identifying contributing factors, and using statistical methods to determine the likelihood of each factor leading to failure. This information is then combined to calculate an overall Probability of Failure.

What factors influence the "Probability of Failure"?

The factors that contribute to the Probability of Failure can vary greatly depending on the system or event being studied. Some common factors include design flaws, material defects, human error, environmental conditions, and equipment malfunctions. These factors can interact with each other in complex ways, making the calculation of Probability of Failure a challenging task.

How can the "Probability of Failure" be reduced?

There are several strategies that can be used to reduce the Probability of Failure. These include improving design and manufacturing processes, implementing quality control measures, conducting thorough risk assessments, and regularly monitoring and maintaining the system or event. In some cases, redundant systems or backup plans can also be put in place to mitigate the impact of failure.

What is the difference between "Probability of Failure" and "Risk"?

While Probability of Failure and Risk are related concepts, they are not the same. Probability of Failure is a measure of the likelihood of a specific event or system failing, while Risk takes into account both the likelihood and the potential consequences of that failure. In other words, Probability of Failure is just one factor that contributes to Risk, along with factors such as severity of consequences and potential mitigation strategies.

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