Are simulation tools ready for big data? Computational experiments with supply chain models developed in Simio

Abstract

Peer-review under responsibility of the scientific committee of the International Conference on Industry 4.0 and Smart Manufacturing. The need and potential benefits for the combined use of Simulation and Big Data in Supply Chains (SCs) has been widely recognized. Having worked on such project, some simulation experiments of the modelled SC system were conducted in SIMIO. Different circumstances were tested, including running the model based on the stored data, on statistical distributions and considering risk situations. Thus, this paper aimed to evaluate such experiments, to evaluate the performance of simulations in these contexts. After analyzing the obtained results, it was found that whilst running the model based on the real data required considerable amounts of computer memory, running the model based on statistical distributions reduced such values, albeit required considerable higher time to run a single replication. In all the tested experiments, the simulation took considerable time to run and was not smooth, which can reduce the stakeholders' interest in the developed tool, despite its benefits for the decision-making process. For future researches, it would be beneficial to test other simulation tools and other strategies and compare those results to the ones provided in this paper.