Wet-etching in wafer fabrication is an automated process involving a complex interplay of mixed intermediate policies and material-handling constraints. Its operation poses a challenging resource-constrained flowshop scheduling problem that is crucial for enhancing productivity, improving yield, and minimizing wafer contamination. A novel continuous-time mixed-integer linear programming (MILP) formulation is presented for sequencing and scheduling wafer lots in an automated wet-etch station (AWS). Several reformulations and constraints are numerically evaluated to identify the best formulation. On the basis of this formulation, a near-optimum two-step strategy that is robust with respect to lot transfer times is developed for solving moderately sized problems.