Pharmaceutical and specialty chemical production often causes high waste to product ratios. This can be explained by complex reaction mechanisms that require complicated multi-step production routes as well as stringent product purity and quality requirements. Therefore, a large number of different types and levels of waste are leaving pharmaceutical production campaigns and need material recovery and/or adequate treatment. The design of waste reduction and pollution prevention efforts is complicated by the variability of the waste loads and compositions as well as the uncertainty associated with federal and local regulations. Therefore, a design methodology including a rigorous treatment of the influence of uncertainty is essential for the design of plant-wide waste management strategies at multi-purpose plants. In this paper, two design aspects will be presented. Earlier work presented a deterministic superstructure synthesis and optimization approach for the automatic waste management [Linninger, A. A., & Chakraborty, A. (1999). Synthesis and optimization of waste treatment flowsheets. Computers & Chemical Engineering, 23, 1415-1425.] Designing plant-wide waste management policies assuming perfect information may not be satisfactory given the variability of the production campaigns. Therefore, this article addresses the problem of finding optimal waste management policies for entire manufacturing sites in the presence of uncertainty. It will offer a mathematical programming framework for implementing three contrasting strategies. Small industrial case studies exemplify the impact of different perspectives on the structural design decisions in the overall plant design. The methodology addresses the need for evaluating uncertainty rigorously and its impact on decision-making for solvent-recovery and treatment options.