Manufacturing execution systems intellectualization: Oil and gas implementation sample

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Up-to-date trend in industrial automation is implementation of Manufacturing Execution Systems (MES) everywhere and in oil and gas industry. Conception of MES is constantly in progress. Many researches suppose that analytical features, available for low-end users (engineers, dispatchers, geologists, etc.) are necessary in manufacturing management, but today there is no ready-to-use framework applicable to make intelligent manufacturing systems for oil and gas industry. A model-driven approach of MES intellectualization and an original iMES framework proposed. iMES based on functions of the traditional MES (within MESA-11 model), business intelligence (BI)-methods (On-Line Analytical Processing & Data Mining) and production markup language (industrial data standard for oil and gas production). Case study of well tests results validation using iMES framework is considered.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages170-177
Number of pages8
Volume6918 LNCS
DOIs
Publication statusPublished - 2011
Event1st International Conference on Model and Data Engineering, MEDI 2011 - Obidos, Portugal
Duration: 28 Sep 201130 Sep 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6918 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other1st International Conference on Model and Data Engineering, MEDI 2011
CountryPortugal
CityObidos
Period28.9.1130.9.11

Fingerprint

Manufacturing
Gases
Gas industry
Industry
Business Intelligence
Markup languages
Competitive intelligence
Intelligent Systems
Automation
Data Mining
Data mining
Gas
Oils
Necessary
Engineers
Model
Framework
Processing

Keywords

  • data mining in industry
  • Intellectual Manufacturing Systems
  • Manufacturing Execution System
  • Manufacturing Process Control

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Bogdan, S., Kudinov, A., & Markov, N. (2011). Manufacturing execution systems intellectualization: Oil and gas implementation sample. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6918 LNCS, pp. 170-177). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6918 LNCS). https://doi.org/10.1007/978-3-642-24443-8_19

Manufacturing execution systems intellectualization : Oil and gas implementation sample. / Bogdan, Stepan; Kudinov, Anton; Markov, Nikolay.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 6918 LNCS 2011. p. 170-177 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6918 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Bogdan, S, Kudinov, A & Markov, N 2011, Manufacturing execution systems intellectualization: Oil and gas implementation sample. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 6918 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6918 LNCS, pp. 170-177, 1st International Conference on Model and Data Engineering, MEDI 2011, Obidos, Portugal, 28.9.11. https://doi.org/10.1007/978-3-642-24443-8_19
Bogdan S, Kudinov A, Markov N. Manufacturing execution systems intellectualization: Oil and gas implementation sample. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 6918 LNCS. 2011. p. 170-177. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-24443-8_19
Bogdan, Stepan ; Kudinov, Anton ; Markov, Nikolay. / Manufacturing execution systems intellectualization : Oil and gas implementation sample. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 6918 LNCS 2011. pp. 170-177 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
@inproceedings{e48a89fea4ed4c66b4daf0bb40b5af50,
title = "Manufacturing execution systems intellectualization: Oil and gas implementation sample",
abstract = "Up-to-date trend in industrial automation is implementation of Manufacturing Execution Systems (MES) everywhere and in oil and gas industry. Conception of MES is constantly in progress. Many researches suppose that analytical features, available for low-end users (engineers, dispatchers, geologists, etc.) are necessary in manufacturing management, but today there is no ready-to-use framework applicable to make intelligent manufacturing systems for oil and gas industry. A model-driven approach of MES intellectualization and an original iMES framework proposed. iMES based on functions of the traditional MES (within MESA-11 model), business intelligence (BI)-methods (On-Line Analytical Processing & Data Mining) and production markup language (industrial data standard for oil and gas production). Case study of well tests results validation using iMES framework is considered.",
keywords = "data mining in industry, Intellectual Manufacturing Systems, Manufacturing Execution System, Manufacturing Process Control",
author = "Stepan Bogdan and Anton Kudinov and Nikolay Markov",
year = "2011",
doi = "10.1007/978-3-642-24443-8_19",
language = "English",
isbn = "9783642244421",
volume = "6918 LNCS",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "170--177",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

}

TY - GEN

T1 - Manufacturing execution systems intellectualization

T2 - Oil and gas implementation sample

AU - Bogdan, Stepan

AU - Kudinov, Anton

AU - Markov, Nikolay

PY - 2011

Y1 - 2011

N2 - Up-to-date trend in industrial automation is implementation of Manufacturing Execution Systems (MES) everywhere and in oil and gas industry. Conception of MES is constantly in progress. Many researches suppose that analytical features, available for low-end users (engineers, dispatchers, geologists, etc.) are necessary in manufacturing management, but today there is no ready-to-use framework applicable to make intelligent manufacturing systems for oil and gas industry. A model-driven approach of MES intellectualization and an original iMES framework proposed. iMES based on functions of the traditional MES (within MESA-11 model), business intelligence (BI)-methods (On-Line Analytical Processing & Data Mining) and production markup language (industrial data standard for oil and gas production). Case study of well tests results validation using iMES framework is considered.

AB - Up-to-date trend in industrial automation is implementation of Manufacturing Execution Systems (MES) everywhere and in oil and gas industry. Conception of MES is constantly in progress. Many researches suppose that analytical features, available for low-end users (engineers, dispatchers, geologists, etc.) are necessary in manufacturing management, but today there is no ready-to-use framework applicable to make intelligent manufacturing systems for oil and gas industry. A model-driven approach of MES intellectualization and an original iMES framework proposed. iMES based on functions of the traditional MES (within MESA-11 model), business intelligence (BI)-methods (On-Line Analytical Processing & Data Mining) and production markup language (industrial data standard for oil and gas production). Case study of well tests results validation using iMES framework is considered.

KW - data mining in industry

KW - Intellectual Manufacturing Systems

KW - Manufacturing Execution System

KW - Manufacturing Process Control

UR - http://www.scopus.com/inward/record.url?scp=80054808444&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=80054808444&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-24443-8_19

DO - 10.1007/978-3-642-24443-8_19

M3 - Conference contribution

AN - SCOPUS:80054808444

SN - 9783642244421

VL - 6918 LNCS

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 170

EP - 177

BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

ER -