| Title |
Requirements Engineering for an Industrial Symbiosis Tool for Industrial Parks Covering System Analysis, Transformation Simulation and Goal Setting |
| ID_Doc |
18509 |
| Authors |
Lütje, A; Wohlgemuth, V |
| Title |
Requirements Engineering for an Industrial Symbiosis Tool for Industrial Parks Covering System Analysis, Transformation Simulation and Goal Setting |
| Year |
2020 |
| Published |
Administrative Sciences, 10.0, 1 |
| DOI |
10.3390/admsci10010010 |
| Abstract |
Industrial Symbiosis (IS) is a collaborative cross-sectoral approach to connect the resource supply and demand of various industries in order to optimize the resource use through exchange of materials, energy, water and human resources across different companies, while generating ecological, technical, social and economic benefits. One of the main goals of IS is the set-up of advanced circular/cascading systems, in which the energy and material flows are prolonged for multiple utilization within industrial systems in order to increase resource productivity and efficiency, while reducing the environmental load. Many Information Communication Technology (ICT) tools have been developed to facilitate IS, but they predominantly focus on the as-is analysis of the IS system, and do not consider the development of a common desired target vision or corresponding possible future scenarios as well as conceivable transformation paths from the actual to the defined (sustainability) target state. This gap shall be addressed in this paper, presenting the software requirements engineering results for a holistic IT-supported IS tool covering system analysis, transformation simulation and goal-setting. This new approach goes beyond system analysis and includes the use of expert systems, system dynamics and Artificial Intelligence (AI) techniques, which turn the IT-supported IS tool to be developed into a comprehensive and holistic instrument with which future scenarios and transformation paths can be simulated. |
| Author Keywords |
Industrial Symbiosis; Industrial Ecology; expert system; Artificial Intelligence; Machine Learning; Agent-Based Modelling; system dynamics; resource efficiency; resource productivity |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Emerging Sources Citation Index (ESCI) |
| EID |
WOS:000525951500009 |
| WoS Category |
Management |
| Research Area |
Business & Economics |
| PDF |
https://www.mdpi.com/2076-3387/10/1/10/pdf?version=1585292203
|