This research is focused on developing a methodology to optimize processes for sustainability. To design a sustainable process that addresses economic, environmental and social concerns is a complex multiobjective problem. Current state of research is restricted to optimizing processes for profit while satisfying environmental regulations and/or measuring the sustainability of the process using already developed tools. There is no methodology that optimizes a process for being sustainable. There is an increasing need to fill the gap between solving a complicated multiobjective problem for sustainability concerns and a simple single objective problem of profit. This research therefore converts the multiobjective problem of designing processes for being sustainable into a single objective problem by using a method of constraints and a method of weights to combine the objective functions. The methodology combines information from an OSU developed SUSTAINABILITY EVALUATOR and uses a commercially available sequential modular simulator Aspen Plus to optimize processes.

The base case of a process is simulated in Aspen Plus and evaluated using the SUSTAINABILITY EVALUATOR. A sensitivity analysis is conducted to determine the variables affecting the product yields, health impact, mass productivity and profit. A FORTRAN code is written to define the objectives in Aspen Plus. A payoff table was generated by optimizing the three individual objectives of profit, health impact and mass productivity. As a next step a multiobjective optimization problem was formulated these three objectives. This was reduced to a single objective problem by using a method of constraints and a method of weights. The constraints are determined using information from the payoff table. The weights were varied from 0 to 1 for each of the objectives. This single objective problem was solved using readily available commercial process simulators such as Aspen Plus. Only the non-dominated set of solutions is presented to a decision maker for choice. The selected solution is compared with a base case using an amoeba chart. By converting a multiobjective problem to a single objective problem a tradeoff between effort and result is achieved. The above methodology is implemented on an Allyl Chloride manufacturing process.