A Methodology for Generating a Digital Twin for Process Industry: A Case Study of a Fiber Processing Pilot Plant
Digital twins are now one of the top trends in Industry 4.0, and many companies are using them to increase their level of digitalization, and, as a result, their productivity and reliability. However, the development of digital twins is difficult, expensive, and time consuming. This article proposes...
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9783203/ |
| _version_ | 1811257257285910528 |
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| author | Mohammad Azangoo Lotta Sorsamaki Seppo A. Sierla Teemu Matasniemi Miia Rantala Kari Rainio Valeriy Vyatkin |
| author_facet | Mohammad Azangoo Lotta Sorsamaki Seppo A. Sierla Teemu Matasniemi Miia Rantala Kari Rainio Valeriy Vyatkin |
| author_sort | Mohammad Azangoo |
| collection | DOAJ |
| description | Digital twins are now one of the top trends in Industry 4.0, and many companies are using them to increase their level of digitalization, and, as a result, their productivity and reliability. However, the development of digital twins is difficult, expensive, and time consuming. This article proposes a semi-automated methodology to generate digital twins for process plants by extracting process data from engineering documents using text and image processing techniques. The extracted information is used to build an intermediate graph model, which serves as a starting point for generating a model in a simulation software. The translation of a graph-based model into a simulation software environment necessitates the use of simulator-specific mapping rules. This paper describes an approach for generating a digital twin based on a steady state simulation model, using a Piping and Instrumentation Diagram (P&ID) as the main source of information. The steady state modeling paradigm is especially suitable for use cases involving retrofits for an operational process plant, also known as a brownfield plant. A methodology and toolchain is proposed, consisting of manual, semi-automated and fully automated steps. A pilot scale brownfield fiber processing plant was used as a case study to demonstrate our proposed methodology and toolchain, and to identify and address issues that may not occur in laboratory scale case studies. The article concludes with an evaluation of unresolved concerns and future research topics for the automated development of a digital twin for a brownfield process system. |
| first_indexed | 2024-04-12T17:53:40Z |
| format | Article |
| id | doaj.art-5dadcab2a4e647658ebc6b672701dd6f |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-12T17:53:40Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-5dadcab2a4e647658ebc6b672701dd6f2022-12-22T03:22:25ZengIEEEIEEE Access2169-35362022-01-0110587875881010.1109/ACCESS.2022.31784249783203A Methodology for Generating a Digital Twin for Process Industry: A Case Study of a Fiber Processing Pilot PlantMohammad Azangoo0https://orcid.org/0000-0001-9789-1126Lotta Sorsamaki1Seppo A. Sierla2https://orcid.org/0000-0002-0402-315XTeemu Matasniemi3Miia Rantala4https://orcid.org/0000-0001-7928-6774Kari Rainio5Valeriy Vyatkin6https://orcid.org/0000-0002-9315-9920Department of Electrical Engineering and Automation, Aalto University, Helsinki, FinlandVTT Technical Research Center of Finland, Espoo, FinlandDepartment of Electrical Engineering and Automation, Aalto University, Helsinki, FinlandVTT Technical Research Center of Finland, Espoo, FinlandSemantum Oy, Espoo, FinlandVTT Technical Research Center of Finland, Espoo, FinlandDepartment of Electrical Engineering and Automation, Aalto University, Helsinki, FinlandDigital twins are now one of the top trends in Industry 4.0, and many companies are using them to increase their level of digitalization, and, as a result, their productivity and reliability. However, the development of digital twins is difficult, expensive, and time consuming. This article proposes a semi-automated methodology to generate digital twins for process plants by extracting process data from engineering documents using text and image processing techniques. The extracted information is used to build an intermediate graph model, which serves as a starting point for generating a model in a simulation software. The translation of a graph-based model into a simulation software environment necessitates the use of simulator-specific mapping rules. This paper describes an approach for generating a digital twin based on a steady state simulation model, using a Piping and Instrumentation Diagram (P&ID) as the main source of information. The steady state modeling paradigm is especially suitable for use cases involving retrofits for an operational process plant, also known as a brownfield plant. A methodology and toolchain is proposed, consisting of manual, semi-automated and fully automated steps. A pilot scale brownfield fiber processing plant was used as a case study to demonstrate our proposed methodology and toolchain, and to identify and address issues that may not occur in laboratory scale case studies. The article concludes with an evaluation of unresolved concerns and future research topics for the automated development of a digital twin for a brownfield process system.https://ieeexplore.ieee.org/document/9783203/Digital twinprocess industrymodelingsteady state simulationimage recognitiontext recognition |
| spellingShingle | Mohammad Azangoo Lotta Sorsamaki Seppo A. Sierla Teemu Matasniemi Miia Rantala Kari Rainio Valeriy Vyatkin A Methodology for Generating a Digital Twin for Process Industry: A Case Study of a Fiber Processing Pilot Plant IEEE Access Digital twin process industry modeling steady state simulation image recognition text recognition |
| title | A Methodology for Generating a Digital Twin for Process Industry: A Case Study of a Fiber Processing Pilot Plant |
| title_full | A Methodology for Generating a Digital Twin for Process Industry: A Case Study of a Fiber Processing Pilot Plant |
| title_fullStr | A Methodology for Generating a Digital Twin for Process Industry: A Case Study of a Fiber Processing Pilot Plant |
| title_full_unstemmed | A Methodology for Generating a Digital Twin for Process Industry: A Case Study of a Fiber Processing Pilot Plant |
| title_short | A Methodology for Generating a Digital Twin for Process Industry: A Case Study of a Fiber Processing Pilot Plant |
| title_sort | methodology for generating a digital twin for process industry a case study of a fiber processing pilot plant |
| topic | Digital twin process industry modeling steady state simulation image recognition text recognition |
| url | https://ieeexplore.ieee.org/document/9783203/ |
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