Dealing with temporality on actions presents an important challenge to AI planning. Unlike Graphplan-based planners which alternate levels of propositions and actions in a regular way, introducing temporality on actions unbalance this symmetry. This paper presents TPSYS, a Temporal Planning SYStem, which arises as an attempt to combine the ideas of Graphplan and TGP to solve temporal planning problems more efficiently. TPSYS is based on a three-stage process. The first stage, a preprocessing stage, facilitates the management of constraints on duration of actions. The second stage expands a temporal graph and obtains the set of temporal levels at which propositions and actions appear. The third stage, the plan extraction, obtains the plan of minimal duration by finding a flow of actions through the temporal graph. The experiments show the utility of our system for dealing with temporal planning problems.