Symbolic BDD-based verification techniques successfully tackle combinatorial explosion in many cases. However, the models to be verified become increasingly larger and more complex, including - for instance - additional features like quantitative requirements and/or a very high number of components. The need to improve performances for verification tools thus remains a challenge. In this work, we extend the framework of Instantiable Transition Systems in order to (i) take into account time constraints in a model and (ii) capture the symmetry of instances which share a common structure, thus significantly increasing the power of our tool. For point (i), we implement timed models with discrete time semantics and for (ii), we introduce scalar sets as a special form of composition. We also report on experiments including comparisons with other tools. The results show a good scale up for our approach.