Beer is one of the most consumed products on the planet (even in the pandemic scenario by . The manufacture of craft beers corresponds to an interesting sector for the economy of any country. However, this does not exempt anyone from going through complicated situations, such as what happened at the Backer brewery and its product contamination process. So, this paper aims to demonstrate the implementation of a discrete event modeling and simulation process, based on stochastic timed petri nets (STPN) for a gluten-free craft beer manufacturing process. The developed tool was submitted to uniform and exponential distribution functions. Its operation was weighted by a real manufacturing process for the specific type of beer evaluated. The simulator demonstrated the ability to abstract all the stages of product manufacture. In addition, the tool was able to understand both distribution functions that the manufacturing process can assume, through a literature tool, STPN. This process can be applicable in small entrepreneurs., which sometimes cannot afford (or do not understand how it works) simulation software.
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