(426c) Discovery and Assessment of Integrated Waste Biorefinery Paths with Conventional Industry Using an Ontology Engineering Approach

The environmental impacts caused by the extensive use of decreasing fossil fuels has brought tremendous attention towards valorisation of renewable and untapped resources such as urban and industrial wastes. The need to reduce the use of virgin resources gives rise in research areas such as waste Industrial Symbiosis (IS), waste biorefineries, and circular economies. The chemistries or else known as â??synthesis pathsâ?, able to extract materials from wastes can be considered abundant.

Unwanted residues are multicomponent materials, containing valuable platform chemicals and numerous added-value specialties. If recovered, they can become standalone feedstock or be also integrated with alike feedstocks to be processed by existing industrial facilities. Such sustainable, retrofitting practice will enlarge process capacity, benefiting from economies of scale, improve LCA performance and cost-effectiveness originating from wasteâ??s off-market prices.

To achieve such task, a) to appropriately integrate waste resources with virgin feedstocks and b) to identify suitable alternative synthesis paths, producing a diverse gamut of bio-based products, requires the combined use of two well-established research fields: ontology engineering and mathematical optimization. Therefore, it is firstly required a large well-structured database to organize knowledge such as waste properties and valorising technologies characteristics, thus achieving interoperability of information across various manufacturing organizations and processing facilities. Secondly, a screening-level decision support platform is necessary to holistically assess waste synthesis paths.

This work provides a framework that merges an ontological based platform with an optimization process systems tool to first organize and manage tacit knowledge such as chemistries, process models, paths, technology specifications, feedstock characteristics etc. for knowledge sharing across diverse users, and secondly to discover the optimum synthesis path according to a set of environmental, economic, and technical objectives. The semantic algorithm is used to establish layers of interactions and translate process models into networks that are further fathomed using optimization and superstructure technology.