The inclusion of production and maintenance objectives in an overall decision-making approach remains as well an academic challenge as a response to a real industrial need. Based on the observation of mutual dependence between production planning and the stochastic variability of the system production performance due to degradation, we propose in this paper a strategy for optimizing both tactical production planning and maintenance under feasibility constraint. The strategy is driven by an iterative two-unit algorithm. The first unit performs the Master Production Schedule optimization whereas the second unit provides an estimation of the feasibility indicators via a stochastic simulation-based approach. Mathematical framework and the proposed iterative algorithm are directly integrated in friendly-user interface software for optimizing the methodology usability in an industrial context.