Failure rate of a system at time 't'

In summary, the failure rate of a system at time t is given by λ(t). The failure rate is estimated using two models, λ0 and αβ. The first model, λ0, uses a constant α and the second model, αβ, uses a function of α.
  • #1
francisg3
32
0
I need to solve the following problem for a school assignment.

Let λ(t) denote the failuer rate of a system at time 't'. The failure rate is simple the number of failures in unit time. For example, if the unit time is one day, then λ is the average of failures per day. Let μ(t) denote the total number of failures from the first release (time t=0) until the current time, 't'. Then we have

(1) λ= dμ/dt

(2) μ = ∫λ(T) where the limits of integration are T=0 (lower) and T=t (upper)

Two models are used for estimating λ and μ. In the forumlae below, λ0 is the failure rate at time t=0, and α and β are constants

λ=λ0(1-μ/α)

λ=λ0e^- β μ



Use (1) or (2) to find λ and μ as functions of time for each model.



...I just need some direction. Thanks!
 
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  • #2
for the case 1

[tex] \lambda = \lambda_o (1-\frac{\mu}{\alpha})[/tex]

[tex] \frac{d\mu}{dt}=\lambda_o(1-\frac{\mu}{\alpha})[/tex]

[tex] \frac{d\mu}{\left(1-\frac{\mu}{\alpha}\right)}=\lambda_o \,\, dt [/tex]

now integrate within the given limits
 
  • #3
so the resulting integration would be:

-α ln (μ -α) evaluated at 0 and 't' correct?
 
  • #4
no...check the integration...remember to integrate both sides

and francis, i see that you have doubled up this thread...two threads are off
by half an hour. This is NOT a good practice. Somebody will report this to the mods.

Another thread going at

https://www.physicsforums.com/showthread.php?t=483138
 
  • #5
I know I double posted, realized that this was not homework/coursework section but I don't know how to delete a post. Sorry.
 
  • #6
I am also having problems with this question, I integrated:

[itex]\int\frac{dμ}{(1-\frac{μ}{α})}[/itex] = [itex]\int[/itex][itex]\lambda[/itex]0dt

And I got:

-αln(μ-α) = [itex]\lambda[/itex]0t

I'm not sure if this is going in the right direction and what would I have to do after this in order to find μ(t) and λ(t)?

Thanks
 
  • #7
kazo, use properties of logarithm...

[tex]-\alpha \ln (\mu-\alpha)=\lambda_o t [/tex]

[tex] \ln (\mu-\alpha)=-\frac{\lambda_o t}{\alpha}[/tex]

[tex]\mu-\alpha= \mbox{exp}\left[-\frac{\lambda_o t}{\alpha}\right ] [/tex]

[tex]\mu (t) =\alpha +\mbox{exp}\left[-\frac{\lambda_o t}{\alpha}\right ] [/tex]

and plug this to get [itex]\lambda[/itex] as function of t
 
  • #8
Forgot a +C. That's important.
 

1. What does the term "failure rate" mean?

The failure rate of a system at time 't' refers to the frequency at which the system experiences failures or malfunctions over a certain period of time. It is often measured as the number of failures per unit of time or as a probability of failure occurring within a given time frame.

2. How is the failure rate of a system calculated?

The failure rate of a system can be calculated by dividing the number of failures that occur within a specific time period by the total number of hours or units of operation during that time period. This can be expressed as a failure rate per unit time, such as failures per hour or per million hours of operation.

3. What factors can influence the failure rate of a system?

The failure rate of a system can be influenced by a variety of factors, including the design and quality of the system components, the operating conditions and environment, and the frequency and type of maintenance and repairs performed on the system.

4. How can the failure rate of a system be improved?

To improve the failure rate of a system, it is important to identify and address any underlying issues or weaknesses in the system design or components. Regular maintenance and testing can also help to identify potential failures before they occur and prevent them from happening.

5. How can the failure rate of a system be predicted?

The failure rate of a system can be predicted using various reliability engineering techniques, such as statistical analysis and modeling. These methods take into account factors such as component failure rates, system design, and operating conditions to estimate the likelihood of failures occurring within a certain time frame.

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