Robustness Evaluation Process for Scheduling under Uncertainties

Scheduling production is an important decision issue in the manufacturing domain. With advent of era Industry 4.0, basic generation schedules becomes no longer sufficient to face new constraints flexibility and agility that characterize architecture systems. In this context, must take into account increasingly disrupted environment while maintaining a good performance level. This paper contributes identified field smart scheduling by proposing complete process for assessing robustness schedule solutions: i.e., its ability resist uncertainties. focuses on helping maker choosing best strategy be implemented. It aims at considering impact uncertainties predictive schedules. Moreover, it assumed data upcoming from connected workshops are available, such can modelled stochastic variables supported timed automata modelling these The proposed approach thus based Stochastic Discrete Event Systems models model checking techniques defining highly reusable modular process. solution illustrated academic example (generecity scalability) deeply evaluated using statistical analysis. application evaluation technological opportunities offered 4.0.