Reliability Prediction using Monte Carlo Simulation
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- čas přidán 17. 07. 2019
- Dear friends,
In the last video on stress-strength interference, we have seen the analytical method. This has limitations and often cannot be used in real life problems in reliability prediction. For example, velocity of windmill may have Weibull or lognormal distribution, elevators may have particular application load cycles which can only be modelled using empirical distributions. In such situations, we need to use Monte Carlo Simulation using various other distributions. I will discuss and explain this technique in this video.
Thank you very much for a detailed explanation!
Thank you!😊
Thank you
My pleasure!
Hello sir, thank you
I have one question. same objective can be met in Stress - Strength interfernece theory right ?. why monte carlo is used ?
Hello Arun Kumar, Monte Carlo is required if analytical solution is not possible.
Sir, Thank you very much for presenting this topic. Using a mathematical model, I have estimated values of the model i.e aircraft velocity, position etc. Now I have to verify whether the estimated model is robust against uncertainties. I have estimated data and true sensor data. Could you please share your idea to perform the MCS with the above mentioned information? Thanks in advance...
Apologies for my late response. Please write an email on ioqr@world-class-quality.com with more details.
Reliability per load application? If you could explain the time unit here? Is it per load? How can we relate it to life cycle of the product? Can we have any governing equation here?
Yes. It is per load cycle. Each load cycle will vary as per the randomness with the distribution. For life cycles, you need to raise it to the power.
Thank you for video. But I'd like to hear a better voice quality. It's hard to understand words somitimes.
Yes. You are correct. We have made improvement in the later videos. Apologize for this!