Marija Jankovic

A DATA-AND KNOWLEDGE-DRIVEN METHODOLOGY FOR GENERATING ECO-INDUSTRIAL PARK ARCHITECTURES

Industrial symbiosis can be understood as the substitution of new resources used in an industrial process by another resource that would otherwise be discarded. Industrial symbiosis can thereby create new revenue streams and at the same time reduce environmental impact. The initial step in creating an industrial symbiosis is the identification of potential substation relationships between production plants. This step is challenging, as information about the companies is often not available. Several software tools have been developed in order to identify potential symbiosis opportunities. However, these tools have the shortcoming that they require extensive data input from companies owning the production plants. This requirement limits the number of companies for which symbiosis opportunities are identified. In this paper, we propose a data-driven methodology for identifying industrial symbiosis and generating eco-industrial park architectures. The methodology is based on meta-models of industrial plants for identifying plant attributes for certain types of plants, correlations that estimate the rough amount of resource supply and demand of a plant, and a rule-based system that identifies symbiosis opportunities based on knowledge from successful symbioses. Based on the symbiosis opportunities, approach generates eco-industrial park architectures that are optimal in terms of economic and environmental performance. Finally, we apply the methodology to a case study of the existing Kalundborg eco-industrial park to evaluate if the methodology is capable of finding existing symbioses. We conclude that the methodology can be applied to screening industrial zones with standard types of industrial plants. However, the results depend on the types of existing industrial plant meta-models in the database. Future work will focus on extending the data and knowledge base; and validating the methodology by its application to other existing eco-industrial parks.

Towards an Automatized Generation of Rule-Based Systems for Architecting Eco-Industrial Parks

In this article we present the matchmaking problem in industrial symbiosis where wastes from one company are matched with resources of another company that could be substituted. Identifying potential matches is difficult, as it is based on knowledge that certain wastes can substitute certain resources. Capturing this knowledge in the form of waste-resource matching rules manually is time-consuming. Therefore, we argue that a Natural Language Processing (NLP)-based approach of semi-automatically extracting rules from domain-specific data sets could be a viable approach to solving this problem. The basic NLP problem to solve is to find similar concepts (synonyms), part-whole relationships (meronyms), and “is a” relationships (hyponyms). Synonyms are important for finding wastes and resources that are named differently but refer to the same object. For example, water and its chemical formula H2O are often used interchangeably. Meronyms are part-whole relationships that may help to identify wastes with components that could be used as a resource. For example, methane is a component of natural gas. Hyponyms allow for building taxonomies. For example, wood is a kind of biomass. We present the results of an initial literature survey of algorithms that are able to find these relationships in large sets of unstructured text documents. Furthermore, we propose a research approach for further extending the literature survey and testing the existing algorithms on small test cases and a realistic matchmaking case. For future work, additional problems that fall into the NLP category can be addressed such as semi-automatically identifying processes for converting wastes into resources.

Value Proposition Design for Systems and Services by Adapting Affordance-Based Design

In early design stages, firms need to generate and assess their value propositions. Although both business developers and systems engineers capture customers’ needs to design the value proposition, they suffer from inefficient business and engineering processes interactions. Moreover, they lack methods to elicit the needs in a structured way and to explore the best value propositions. n nWe propose to extend the affordance-based design for systems and services in order support the elicitation and capture of stakeholders’values; and to identify boundaries of the system design problem to explore the best value propositions. Hence, affordances — which describe what system provides to other systems and stakeholders — help to frame the context. Today, affordance-based design is mainly used for artifact design. We propose to extend this approach to systems and services and complement it with a focus on stakeholders’ activities and external systems’ stages. With regard to the different system design perimeters defined by affordances, value propositions are designed. The proposed method is illustrated on an AIRBUS Defence & Space innovative project.