Optimization of Kanban systems using robust parameter design: a case of study

The current competitive market demands that manufacturing companies have a survival strategy which should totally focus on providing high-quality products, being consistent in the level of service provided, having lower inventory levels and higher flexibility in operations. In this context, Kanban can be classified as a tool that assists in the proper sizing of inventory levels and production control of the system. However, numerous studies have been developed with the aim of reliably reducing stock levels in Kanban supermarkets, yielding different optimization techniques, but for fixed demands. This work proposes the minimization solution of the supermarket from randomly different demands, using environments with simulated experiments from the ARENA® software, from a response surface methodology (RSM) along with a weighted minimization of the mean standard error and compare with the results provided by the use of optimizer Arena OptQuest®, thus, it is possible to evaluate the robustness question.