A service oriented system of reusable algorithms for distributed control of petroleum facilities in onshore oilfields

Dobrescu, Sorin; Chenaru, Oana; Matei, Nicoleta; Ichim, Loretta; Popescu, Dan

doi:10.1109/ecai.2016.7861115

Search citation statements

Order By: Relevance

Paper Sections

Select...

Production1

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2019

2024

Publication Types

Select...

Article5

Relationship

Self Cite0

Independent5

Authors

Journals

Cited by 8 publications

(1 citation statement)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…They concluded that their proposed system can meet the dynamic operating conditions of oil and gas fields to conform to the present and future requirements with a reduced environmental impact and greater economic pay-offs. Dobrescu et al [12] presented a MAS framework for shared control of petroleum services for onshore oilfields. The authors proposed a distributed control strategy for a basic production system based on the IEC 61499 standard.…”

Section: Productionmentioning

confidence: 99%

Machine learning and multi-agent systems in oil and gas industry applications: A survey

Hanga

Kovalchuk

2019

Computer Science Review

120

View full text Add to dashboard Cite

Section: Productionmentioning

confidence: 99%

Machine learning and multi-agent systems in oil and gas industry applications: A survey

Hanga

Kovalchuk

2019

Computer Science Review

120

View full text Add to dashboard Cite

Deriving secondary traits of industry 4.0: A comparative analysis of significant maturity models

Simetinger

Zhang

2020

Syst Res Behav Sci

View full text Add to dashboard Cite

The potential of Industry 4.0 concept is represented by increased productivity, improved cost efficiency, or higher product attractiveness. The adoption of this concept is related to a high number of challenges and risks. A possible solution to address these challenges and risks is the adoption or implementation of this concept using the maturity models. The maturity models use various approaches to Industry 4.0 with concepts and procedures varying in every maturity model. However, there still exist divergences in terms of their impact on the organizational units. This research conducts the comparative analysis of significant maturity models to identify generally shared traits of Industry 4.0 that are common to the majority of the analyzed maturity models. In addition, it discusses the impact of Industry 4.0 on the business informatics unit in organizations.

show abstract

A pilot study: An assessment of manufacturing SMEs using a new Industry 4.0 Maturity Model for Manufacturing Small- and Middle-sized Enterprises (I4MMSME)

Simetinger

Basl

2022

Procedia Computer Science

View full text Add to dashboard Cite

A service oriented system of reusable algorithms for distributed control of petroleum facilities in onshore oilfields

Cited by 8 publications

References 6 publications

Machine learning and multi-agent systems in oil and gas industry applications: A survey

Machine learning and multi-agent systems in oil and gas industry applications: A survey

Deriving secondary traits of industry 4.0: A comparative analysis of significant maturity models

A pilot study: An assessment of manufacturing SMEs using a new Industry 4.0 Maturity Model for Manufacturing Small- and Middle-sized Enterprises (I4MMSME)

Contact Info

Product

Resources

About