| Scope and method of study. The purpose of this study is to develop a comprehensive methodology that considers the uncertainties present when evaluating process alternatives to reduce the waste generated in a chemical process. After conducting a characterization and environmental impact study, the methodology identifies waste minimization options through experimental design techniques and methods of structured thinking. Under a decision theory framework, the alternatives selected are evaluated using two competing criteria: maximize profit and minimize the environmental impact. The former is measured using the annual equivalent profit method that includes the typical process related costs and the environmental related costs. The second criterion is measured using an environmental impact index based on the release potential of a process stream and its toxicological characteristics. Considering the uncertainties present when evaluating process alternatives and the two objectives used in this evaluation, the methodology incorporates a multiple objective stochastic optimization algorithm, using the process simulator ASPEN PLUSTM, that results in a combination of the compromise programming approach and the stochastic annealing algorithm. The production of methyl chloride by the thermal chlorination of methane is used as a case study to evaluate the proposed methodology.; Findings and conclusions. A unique methodology was developed that incorporates multiple objective optimization techniques and stochastic programming methods. This was accomplished using the process simulator ASPEN PLUSTM and combining the compromise programming approach and the stochastic annealing algorithm. The economic performance of the alternatives evaluated is a key criterion. Therefore, a detailed description of the environmental and process related costs is included in the study. The proposed methodology was successfully applied to the production of methyl chloride by the thermal chlorination of methane. This process was optimized for two competing objectives considering three continuous variables, one binary variable, and four uncertain parameters. |
