Digital reality of oil refining

UDK: УДК 665.62:65.011.56
DOI: DOI: 10.24887/0028-2448-2021-11-67-71
Key words: digitalization, digital twin, digital factory, improved business performance, business objectives, virtual reality, augmented reality, digital initiative
Authors: E.S. Golovina1, M.A. Litvinenko2, Yu.A. Ergomyshev1, V.A. Lavrentiev1, A.V. Komogorov1, I.N. Khaimovich3 1Samaraneftekhimproekt JSC, RF, Samara 2Rosneft Oil Company, RF, Moscow 3Samara National Research University named after Academician S.P. Korolev, RF, Samara

The article addresses various aspects of companies digitalization with respect to the regulatory documents of the Russian Federation and as applied to major companies program documents. The authors make the point that at present, in spite of the numerous documents, there is no generally accepted concept of digitalization or of its components; each company has its own understanding of the term. At the same time, the major companies realize that digitalization must not be carried out for its own sake. Digitalization is the tool for improving business performance. The article describes the evolution of the concept ‘digital twin’. It points out that a number of data resources can be used for entering data into the digital twin, e.g., the theoretical background, real data from the facility obtained by means of physical sensors, or from virtual analyzers, external ports, and other sources. Because the digital twin is used for predicting the facility operation in various conditions to optimize the real facility, then, eventually, carrying out virtual testing instead of real testing should result in more effective processes. A digital company or a digital factory in particular is not a three-dimensional model with excessive data, but a set of interrelated digital initiatives in which each of the initiatives improves business performance. The authors offer an explanation why it is only by gradual preparation of the company for digital transformation and by systematic implementation of the digitalization road map that real results can be achieved. The authors give examples of the various ways of applying predictive analytics to gradual digitalization of production, as well as examples of incorporating virtual/augmented reality into training courses that employ models based on digital twin.

References

1. Tao F. et al., Digital twin in industry: State-of-the-art, IEEE Transactions on Industrial Informatics, 2018, V. 15, no. 4, pp. 2405–2415, DOI:10.1109/TII.2018.2873186

2. Borovkov A.I. et al., Digital twins and digital transformation of defense industry enterprises (In Russ.), Vestnik Vostochno-Sibirskoy otkrytoy akademii, 2019, V. 32.

3. Ponomarev K.S., Feofanov A.N., Grishina T.G., Enterprise digital twin - instrument of digitalization the activity of the organization (In Russ.), Avtomatizatsiya i modelirovanie v proektirovanii i upravlenii, 2019, no. 2(4), DOI: 10.30987/article_5cf2d1c56f8944.09486334

4. Danilov-Danil'yan V.I., Ecology, hydrology, digitalization, digital twins and the elementary truths of modeling methodology (In Russ.), Collected “Nauchnye problemy ozdorovleniya rossiyskikh rek i puti ikh resheniya” (Scientific problems of rehabilitation of Russian rivers and ways to solve them), 2019, pp. 497–502.

5. Kulagin V., Sukharevski A., Meffert Yu., Nastol'naya kniga po tsifrovizatsii biznesa (Business digitalization handbook), Moscow: Intellektual'naya Literatura Publ., 2019, 293 p.

6. Khaimovich I.N., Ramzaev V.M., Razrabotka modeli dannykh dlya funktsionirovaniya proizvodstvennykh aktivnykh elementov na osnove informatsionnogo vzaimodeystviya (Development of data model for production active elements functioning on the basis of information interaction), IV International conference and youth school “Informatsionnye tekhnologii i nanotekhnologii” (Information technology and nanotechnology), 2018, pp. 2149-2158.

7. Pavlov V.A. et al., Prospects for applying virtual simulators to hazardous production (In Russ.), Neftyanoe khozyaystvo = Oil Industry, 2020, no. 11, pp. 70–72, DOI: 10.24887/0028-2448-2020-11-70-72

The article addresses various aspects of companies digitalization with respect to the regulatory documents of the Russian Federation and as applied to major companies program documents. The authors make the point that at present, in spite of the numerous documents, there is no generally accepted concept of digitalization or of its components; each company has its own understanding of the term. At the same time, the major companies realize that digitalization must not be carried out for its own sake. Digitalization is the tool for improving business performance. The article describes the evolution of the concept ‘digital twin’. It points out that a number of data resources can be used for entering data into the digital twin, e.g., the theoretical background, real data from the facility obtained by means of physical sensors, or from virtual analyzers, external ports, and other sources. Because the digital twin is used for predicting the facility operation in various conditions to optimize the real facility, then, eventually, carrying out virtual testing instead of real testing should result in more effective processes. A digital company or a digital factory in particular is not a three-dimensional model with excessive data, but a set of interrelated digital initiatives in which each of the initiatives improves business performance. The authors offer an explanation why it is only by gradual preparation of the company for digital transformation and by systematic implementation of the digitalization road map that real results can be achieved. The authors give examples of the various ways of applying predictive analytics to gradual digitalization of production, as well as examples of incorporating virtual/augmented reality into training courses that employ models based on digital twin.

References

1. Tao F. et al., Digital twin in industry: State-of-the-art, IEEE Transactions on Industrial Informatics, 2018, V. 15, no. 4, pp. 2405–2415, DOI:10.1109/TII.2018.2873186

2. Borovkov A.I. et al., Digital twins and digital transformation of defense industry enterprises (In Russ.), Vestnik Vostochno-Sibirskoy otkrytoy akademii, 2019, V. 32.

3. Ponomarev K.S., Feofanov A.N., Grishina T.G., Enterprise digital twin - instrument of digitalization the activity of the organization (In Russ.), Avtomatizatsiya i modelirovanie v proektirovanii i upravlenii, 2019, no. 2(4), DOI: 10.30987/article_5cf2d1c56f8944.09486334

4. Danilov-Danil'yan V.I., Ecology, hydrology, digitalization, digital twins and the elementary truths of modeling methodology (In Russ.), Collected “Nauchnye problemy ozdorovleniya rossiyskikh rek i puti ikh resheniya” (Scientific problems of rehabilitation of Russian rivers and ways to solve them), 2019, pp. 497–502.

5. Kulagin V., Sukharevski A., Meffert Yu., Nastol'naya kniga po tsifrovizatsii biznesa (Business digitalization handbook), Moscow: Intellektual'naya Literatura Publ., 2019, 293 p.

6. Khaimovich I.N., Ramzaev V.M., Razrabotka modeli dannykh dlya funktsionirovaniya proizvodstvennykh aktivnykh elementov na osnove informatsionnogo vzaimodeystviya (Development of data model for production active elements functioning on the basis of information interaction), IV International conference and youth school “Informatsionnye tekhnologii i nanotekhnologii” (Information technology and nanotechnology), 2018, pp. 2149-2158.

7. Pavlov V.A. et al., Prospects for applying virtual simulators to hazardous production (In Russ.), Neftyanoe khozyaystvo = Oil Industry, 2020, no. 11, pp. 70–72, DOI: 10.24887/0028-2448-2020-11-70-72



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