In this paper, we advocate the use of robust decision trees for the problem of assembly line scheduling problem, which is modeled as a multi-mode resource constrained project scheduling Problem, with uncertainty about activity duration and a resource investment objective. The idea of a robust decision tree is that at each node, the decision maker has access to some information about the ongoing scenario. Depending on the different information they could obtain, a partial solution is proposed. Considering that the level of uncertainty is lowered, the new partial solution is less conservative and improve the robustness guarantee. However, since all accessible information may not be relevant, we turned the information selection part into an optimization problem. We first introduce the industrial context and the problem at stake. Then we propose algorithms to solve the information selection problem, using constraint programming, and then to build such robust decision trees. Finally we provide experimental results for benchmarks instances and industrial instances.