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|Title:||Cross domain clustering of chemical and electrical network in a chemical plant||Authors:||Lee, Bryan Zhen Yuan||Keywords:||Engineering::Electrical and electronic engineering::Electric power::Auxiliaries, applications and electric industries
Engineering::Electrical and electronic engineering::Computer hardware, software and systems
|Issue Date:||2021||Publisher:||Nanyang Technological University||Source:||Lee, B. Z. Y. (2021). Cross domain clustering of chemical and electrical network in a chemical plant. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/148956||Project:||A1049-201||Abstract:||The rise of Industry 4.0 has ushered in an age of digital revolution where software can be used to replicate industrial processes digitally through non-invasive means. This provides users with the ability to simulate specific scenarios within controlled environments and predict possible outcomes that can be used for data analysis and process optimization. One such system that is capable of doing this is the J-Park Simulator (JPS). The JPS, modelled after the Eco Industrial Park of Jurong Island in Singapore, is an ontology-based Semantic Web Service that uses Web Ontology Language (OWL) to replicate the processes and scenarios within the Digital Equivalent of the island. It is modelled to allow interoperability within heterogeneous domains within a parallel world setting. Thus, it can replicate a wide range of scenarios such as carbon measurements, chemical and electrical processes. However, information sharing between separate domains has posed challenges as the concepts and relations between separate domains are not fully defined. There is also a need for cross domain interaction between components from different domains to show how parameters from individual domains affect one another. Therefore, this report proposes the development of a Semantic Web Service that can be used to study the effect of changes between components from the chemical and electrical effects within a chemical plant.||URI:||https://hdl.handle.net/10356/148956||Fulltext Permission:||restricted||Fulltext Availability:||With Fulltext|
|Appears in Collections:||EEE Student Reports (FYP/IA/PA/PI)|
Updated on May 25, 2022
Updated on May 25, 2022
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