An Intelligent Circular Economy Upstream Monitoring & Optimization System Based on Industrial Internet of Things
Anttila, Juha (2019-11-24)
An Intelligent Circular Economy Upstream Monitoring & Optimization System Based on Industrial Internet of Things
Anttila, Juha
(24.11.2019)
Julkaisu on tekijänoikeussäännösten alainen. Teosta voi lukea ja tulostaa henkilökohtaista käyttöä varten. Käyttö kaupallisiin tarkoituksiin on kielletty.
avoin
Julkaisun pysyvä osoite on:
https://urn.fi/URN:NBN:fi-fe2019120545780
https://urn.fi/URN:NBN:fi-fe2019120545780
Tiivistelmä
Industrial Internet of Things (IIoT) has many beneficial applications upon the industry of
Oil and Gas (O&G) and renewable energy production. Renewable energy production is
already growing faster than traditional fossil fuel production. It has been estimated that
the O&G sector can retain its current level of energy production for 40 years with the
already discovered crude oil resources. In order to make sure that energy supply matches
the demand, companies operating in the field of oil and gas are already heavily investing
in energy efficiency, alternative energy processes and products. However, outdated
technologies, legacy systems and prevailing conservative mindset hinder the
development of the industry.
This master’s thesis will be focused on the use of Industrial Internet of Things by the
circular economy upstream which consists of data acquisition, analysis and visualization
across the feedstock exploration and production phases in the field of oil and gas. New
technologies such as cloud computing and analysis will be implemented to the current
environment and further evaluated for the use of prevailing protocols such as OPC-UA
which is the industry-leading communication protocol. The upstream sector will be
evaluated for the purpose of designing, implementing and validating organization-wide
system architecture model and experimental proof-of-concept level IIoT system for
monitoring and optimization of the circular economy industry. The system will be
evaluated and designed to support qualitative measurements such as a liquid fingerprint
in the future. Considering the further use of the raw material, and based on the theoretical
part of this thesis, an experimental prototype level IIoT system will be implemented and
tested in practical terms.
This thesis proves that the analyzed, designed, implemented and verified IIoT monitoring
and optimization system has significant financial and environmentally beneficial results
in the industry of the circular economy. This thesis proves that prevailing outdated
systems can be further developed with modern technologies and solutions which are
extensively described in the organization’s new system architecture model. The final
conclusion indicates that Industry 4.0 and Industrial Internet of Things play a major role
in the monitoring and optimization of the circular economy upstream industry.
Oil and Gas (O&G) and renewable energy production. Renewable energy production is
already growing faster than traditional fossil fuel production. It has been estimated that
the O&G sector can retain its current level of energy production for 40 years with the
already discovered crude oil resources. In order to make sure that energy supply matches
the demand, companies operating in the field of oil and gas are already heavily investing
in energy efficiency, alternative energy processes and products. However, outdated
technologies, legacy systems and prevailing conservative mindset hinder the
development of the industry.
This master’s thesis will be focused on the use of Industrial Internet of Things by the
circular economy upstream which consists of data acquisition, analysis and visualization
across the feedstock exploration and production phases in the field of oil and gas. New
technologies such as cloud computing and analysis will be implemented to the current
environment and further evaluated for the use of prevailing protocols such as OPC-UA
which is the industry-leading communication protocol. The upstream sector will be
evaluated for the purpose of designing, implementing and validating organization-wide
system architecture model and experimental proof-of-concept level IIoT system for
monitoring and optimization of the circular economy industry. The system will be
evaluated and designed to support qualitative measurements such as a liquid fingerprint
in the future. Considering the further use of the raw material, and based on the theoretical
part of this thesis, an experimental prototype level IIoT system will be implemented and
tested in practical terms.
This thesis proves that the analyzed, designed, implemented and verified IIoT monitoring
and optimization system has significant financial and environmentally beneficial results
in the industry of the circular economy. This thesis proves that prevailing outdated
systems can be further developed with modern technologies and solutions which are
extensively described in the organization’s new system architecture model. The final
conclusion indicates that Industry 4.0 and Industrial Internet of Things play a major role
in the monitoring and optimization of the circular economy upstream industry.