This paper aims to perform economic evaluation of scenarios for manufacturing systems via discrete event simulation based experiments. First, three simulation models were built to mimic three manufacturing cells from two companies. In these simulation models, there are eight, thirty two and sixty four scenarios to be economically analyzed. Then, the decision makers can choose the best scenario by selecting the highest net present value, according to a future predicted demand. The research′s results allowed the identification of an activity that should not exist inside the production process (an analyzed scenario). So, the simulation model gained credibility among the decision makers after it pointed out a 35% of increase in the current monthly output. Finally, this work is concluded by highlighting the role of the design of experiments to select the most relevant scenarios to be economically analyzed. This saves time, when there are a large number of scenarios.