| Title |
Smart eco-industrial parks: A circular economy implementation based on industrial metabolism |
| ID_Doc |
3378 |
| Authors |
Gómez, AMM; González, FA; Bárcena, MM |
| Title |
Smart eco-industrial parks: A circular economy implementation based on industrial metabolism |
| Year |
2018 |
| Published |
|
| DOI |
10.1016/j.resconrec.2017.08.007 |
| Abstract |
In order to conserve natural environments, the Circular Economy (CE) is considered as a suitable way to carry out the transition from current economic models to models of a more sustainable nature. From the biological perspective however, industrial systems are generally inefficient. Manufacturing systems from the biological perspective therefore require the incorporation of tools to support decision making, thereby enabling organizations to improve their functions and competitiveness in a global and integrated perspective. Accordingly, at meso level, eco-industrial parks are gaining importance as an approach towards ensuring CE. In this work, an ontological framework for CE, based on industrial metabolism, is developed as the technology for information and knowledge models to share the circularity of resources through industrial ecosystems, based on ecological, economic, and social criteria. The ontology developed is modelled using Ontology Web Language and integrated in an architecture based on bio-inspired Multi-Agent Systems (MAS). Moreover, a quantitative method, Ecological Network Analysis, is incorporated into MAS knowledge to analyze and establish relationships and metabolic pathways between companies, which can increase the circularity of technical nutrients and reduce biological nutrient extraction. The integrated model is applied to a case study on the product life cycle for the establishment of its metabolic pathway through an eco-industrial park. The subsequent incorporation of MAS thereby establishes the Smart Eco-Industrial Park. |
| Author Keywords |
Circular economy; Industrial metabolism; Sustainable manufacturing; Ontology; Multi-Agent system; Ecological network analysis |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:000434902400008 |
| WoS Category |
Engineering, Environmental; Environmental Sciences |
| Research Area |
Engineering; Environmental Sciences & Ecology |
| PDF |
https://idus.us.es/bitstream/11441/153132/3/RCR_martin-gomez_2018_smart_post.pdf
|