Abstract
Selection of optimal technologies for novel biobased products and processes is a major challenge in process design, especially when are considered many alternatives available to transform materials into valuable products. Furthermore, such technological alternatives vary in their technical performances and cause different levels of economic and environmental impacts throughout their life cycles. Additionally, selection of optimal production pathways requires a shift from the traditional materials management practices to more sustainable practices. This contribution provides a method for optimizing multi-product network systems from a sustainability perspective by applying the GREENSCOPE framework as a sustainable objective function. A case study is presented in which the four GREENSCOPE target areas (i.e., efficiency, energy, economics, and environment) are evaluated by 21 preselected indicators as part of a multi-objective optimization problem of a biojet fuel production network. The biojet fuel production network evaluated in this study consists of four main elements: (1) feedstocks management, (2) conversion technologies, (3) co-products upgrading, and (4) auxiliary sections for in situ production of raw materials and utilities. For the sustainability objective function, the 21 indicators are analyzed considering multiple perspectives of stakeholders to study their influence on the decision-making process. It is, different sets of weighting factors are assigned to each of the four target areas. Hence, this sustainability evaluation from different stakeholders' perspectives allows identifying optimal networks, specific target areas with great potential for improvements, and processing steps with great influence in the entire network performance. As a result, diverse optimal network arrangements were obtained according to the multiple stakeholders' perspectives. This evidences that a win-win situation for all sustainability aspects considered can hardly be reached. Finally, this contribution demonstrated the applicability of the proposed methodology for sustainability evaluation, optimization, and decision-making in the context of a multi-product material facility by developing a multi-objective optimization model.