Standard

Methods for Evaluating the Cost-Effectiveness of Using AI for Production Automation. / Vlasov, M.; Lapteva, Anna.
International Scientific Conference on Digital Transformation in Industry: Trends, Management, Strategies, DTI 2022: Conference Proceeding. ed. / V. Kumar; G.L. Kyriakopoulos; V. Akberdina; E. Kuzmin. Springer, 2023. p. 281-296 (Lecture Notes in Information Systems and Organisation; Vol. 61).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Harvard

Vlasov, M & Lapteva, A 2023, Methods for Evaluating the Cost-Effectiveness of Using AI for Production Automation. in V Kumar, GL Kyriakopoulos, V Akberdina & E Kuzmin (eds), International Scientific Conference on Digital Transformation in Industry: Trends, Management, Strategies, DTI 2022: Conference Proceeding. Lecture Notes in Information Systems and Organisation, vol. 61, Springer, pp. 281-296. https://doi.org/10.1007/978-3-031-30351-7_22

APA

Vlasov, M., & Lapteva, A. (2023). Methods for Evaluating the Cost-Effectiveness of Using AI for Production Automation. In V. Kumar, G. L. Kyriakopoulos, V. Akberdina, & E. Kuzmin (Eds.), International Scientific Conference on Digital Transformation in Industry: Trends, Management, Strategies, DTI 2022: Conference Proceeding (pp. 281-296). (Lecture Notes in Information Systems and Organisation; Vol. 61). Springer. https://doi.org/10.1007/978-3-031-30351-7_22

Vancouver

Vlasov M, Lapteva A. Methods for Evaluating the Cost-Effectiveness of Using AI for Production Automation. In Kumar V, Kyriakopoulos GL, Akberdina V, Kuzmin E, editors, International Scientific Conference on Digital Transformation in Industry: Trends, Management, Strategies, DTI 2022: Conference Proceeding. Springer. 2023. p. 281-296. (Lecture Notes in Information Systems and Organisation). doi: 10.1007/978-3-031-30351-7_22

Author

Vlasov, M. ; Lapteva, Anna. / Methods for Evaluating the Cost-Effectiveness of Using AI for Production Automation. International Scientific Conference on Digital Transformation in Industry: Trends, Management, Strategies, DTI 2022: Conference Proceeding. editor / V. Kumar ; G.L. Kyriakopoulos ; V. Akberdina ; E. Kuzmin. Springer, 2023. pp. 281-296 (Lecture Notes in Information Systems and Organisation).

BibTeX

@inproceedings{2651d9093454435bacf7b3c3a7a5085e,
title = "Methods for Evaluating the Cost-Effectiveness of Using AI for Production Automation",
abstract = "The analysis of publications revealed a lack of research on assessing economic indicators when introducing artificial intelligence into technological and production processes. In this regard, the authors aim to find and analyze published methods for assessing the economic effectiveness of automation of production processes using AI. It is rather difficult to evaluate the cost-effectiveness of AI introduced into production for the purpose of automation. Artificial intelligence in automated process control systems is a competitor to deductible means that are the basis of such systems. AI allows improving the quality of a number of functions performed by these means, for example, enhancing the quality of regulation. This, in turn, leads to a rise in the quality of products. However, it is challenging to assess in advance how this event will affect the profitability from the sale of these products. The article developed a methodology for assessing the economic effectiveness of the AI introduction. {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.",
author = "M. Vlasov and Anna Lapteva",
year = "2023",
doi = "10.1007/978-3-031-30351-7_22",
language = "English",
isbn = "978-303130350-0",
series = "Lecture Notes in Information Systems and Organisation",
publisher = "Springer",
pages = "281--296",
editor = "V. Kumar and G.L. Kyriakopoulos and V. Akberdina and E. Kuzmin",
booktitle = "International Scientific Conference on Digital Transformation in Industry: Trends, Management, Strategies, DTI 2022",
address = "Germany",

}

RIS

TY - GEN

T1 - Methods for Evaluating the Cost-Effectiveness of Using AI for Production Automation

AU - Vlasov, M.

AU - Lapteva, Anna

PY - 2023

Y1 - 2023

N2 - The analysis of publications revealed a lack of research on assessing economic indicators when introducing artificial intelligence into technological and production processes. In this regard, the authors aim to find and analyze published methods for assessing the economic effectiveness of automation of production processes using AI. It is rather difficult to evaluate the cost-effectiveness of AI introduced into production for the purpose of automation. Artificial intelligence in automated process control systems is a competitor to deductible means that are the basis of such systems. AI allows improving the quality of a number of functions performed by these means, for example, enhancing the quality of regulation. This, in turn, leads to a rise in the quality of products. However, it is challenging to assess in advance how this event will affect the profitability from the sale of these products. The article developed a methodology for assessing the economic effectiveness of the AI introduction. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

AB - The analysis of publications revealed a lack of research on assessing economic indicators when introducing artificial intelligence into technological and production processes. In this regard, the authors aim to find and analyze published methods for assessing the economic effectiveness of automation of production processes using AI. It is rather difficult to evaluate the cost-effectiveness of AI introduced into production for the purpose of automation. Artificial intelligence in automated process control systems is a competitor to deductible means that are the basis of such systems. AI allows improving the quality of a number of functions performed by these means, for example, enhancing the quality of regulation. This, in turn, leads to a rise in the quality of products. However, it is challenging to assess in advance how this event will affect the profitability from the sale of these products. The article developed a methodology for assessing the economic effectiveness of the AI introduction. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

UR - http://www.scopus.com/inward/record.url?partnerID=8YFLogxK&scp=85163341781

U2 - 10.1007/978-3-031-30351-7_22

DO - 10.1007/978-3-031-30351-7_22

M3 - Conference contribution

SN - 978-303130350-0

T3 - Lecture Notes in Information Systems and Organisation

SP - 281

EP - 296

BT - International Scientific Conference on Digital Transformation in Industry: Trends, Management, Strategies, DTI 2022

A2 - Kumar, V.

A2 - Kyriakopoulos, G.L.

A2 - Akberdina, V.

A2 - Kuzmin, E.

PB - Springer

ER -

ID: 41596047