Economic evaluation of scenarios for manufacturing systems using discrete event simulation based experiments
AbstractThis 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.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors must have a written permission from any third-party materials used in the article, such as figures and graphics. The permission must explicitly allow authors to use the materials. The permission should be submitted with the article, as a supplementary file.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) after BJO&PM publishes it (See The Effect of Open Access).