| Hi-index | 0.00 |
Discrete simulation models are suggested as tools to support reengineering. However, these models cannot identify the nature of the improvements. Furthermore, they are tedious to build when they must be detailed enough to produce accurate evaluations of the improvements impacts. A new system for reengineering that supports the identification of the improvements using benchmarking implemented with fuzzy cognitive maps is presented. This system uses qualitative optimal control models to evaluate the impacts of the improvements and behavior-based learning to reach analysts' agreement. The new system is applied to reengineer a filling line of pharmaceuticals and the results are compared to the ones obtained by optimizing a discrete simulation model of this same line.