Monte Carlo simulation

In german

In this module, you will learn how various distribution models – including the Weibull distribution – can be identified and evaluated in order to gain valuable insights from complex data patterns. You will then learn how to use process capability analyses to evaluate the performance of your processes in a well-founded manner, even with non-normally distributed data. The module also focuses on Monte Carlo simulation. We will introduce you step by step to the procedure for setting up simulation models. We will show you how to integrate both constant and variable input variables into your models in order to create realistic scenarios. Using practical application examples, we will show you how you can minimise uncertainties and make well-founded decisions by using this method.

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Contents

– Distribution models (e.g. Weibull distribution)
– Identification of distributions
– Process capability analysis
– Dealing with non-normally distributed data
– Introduction to Monte Carlo simulation
– Monte Carlo simulation procedure
– Structure of models
– Constant & variable input variables
– Possibilities of simulation
– Examples from practice

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