The impact of changing uncertainty parameters in projects
Dottei, Waldemar (2022)
Diplomityö
2022
School of Engineering Science, Tuotantotalous
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe2022060141673
https://urn.fi/URN:NBN:fi-fe2022060141673
Tiivistelmä
Uncertainty can come in different forms and for different reasons and can have an impact on projects. This requires project managers to know the different methods for planning projects under uncertain conditions, and at best different mathematical models, in order to make predictions and, if necessary, further measures about the course of a project. This study investigates the effect of changing uncertainty parameters in projects through the method of Monte Carlo simulation.
The study was conducted using quantitative methods by experimentally simulating input uncertainty, combining the results with literature reviews. The results show that partially clear stochastic effects can be observed when comparing different parameter changes induced by uncertainty, with other stochastic variables showing no correlation. Furthermore, clear correlations can be shown by which parameter settings the simulation provides more accurate and reliable results. It was also found that it is possible to simulate uncertainty in a meaningful way and that minor changes to the parameters before the simulation, which can arise due to uncertainty, still lead to usable results.
The study was conducted using quantitative methods by experimentally simulating input uncertainty, combining the results with literature reviews. The results show that partially clear stochastic effects can be observed when comparing different parameter changes induced by uncertainty, with other stochastic variables showing no correlation. Furthermore, clear correlations can be shown by which parameter settings the simulation provides more accurate and reliable results. It was also found that it is possible to simulate uncertainty in a meaningful way and that minor changes to the parameters before the simulation, which can arise due to uncertainty, still lead to usable results.