Detail publikace

Generative AI in the manufacturing process: theoretical considerations

DOANH, D. DUFEK, Z. EJDYS, J. GINEVIČIUS, R. KORZYNSKI, P. MAZUREK, G. PALISZKIEWICZ, J. WACH, K. ZIEMBA, E.

Originální název

Generative AI in the manufacturing process: theoretical considerations

Typ

článek v časopise ve Scopus, Jsc

Jazyk

angličtina

Originální abstrakt

The paper aims to identify how digital transformation and Generative Artificial Intelligence (GAI), in particular, affect the manufacturing processes. Several dimensions of the Industry 4.0 field have been considered, such as the design of new products, workforce and skill optimisation, enhancing quality control, predictive maintenance, demand forecasting, and marketing strategy. The paper adopts qualitative research based on a critical review approach. It provides evidence of the GAI technology support in the mentioned areas. Appropriate use of emerging technology allows managers to transform manufacturing by optimising processes, improving product design, enhancing quality control, and contributing to overall efficiency and innovation in the industry. Simultaneously, GAI technologies facilitate predictive analytics to forecast and anticipate future demand, quality issues, and potential risks, improve a marketing strategy and identify market trends.

Klíčová slova

Generative AI; ChatGPT; Industry 4.0; technology; manufacturing processes

Autoři

DOANH, D.; DUFEK, Z.; EJDYS, J.; GINEVIČIUS, R.; KORZYNSKI, P.; MAZUREK, G.; PALISZKIEWICZ, J.; WACH, K.; ZIEMBA, E.

Vydáno

20. 9. 2023

Nakladatel

Sciendo

Místo

Poland

ISSN

2543-6597

Periodikum

Engineering Management in Production and Services

Ročník

15

Číslo

4

Stát

Polská republika

Strany od

76

Strany do

89

Strany počet

14

URL

Plný text v Digitální knihovně

BibTex

@article{BUT186997,
  author="Doung Cong {Doanh} and Zdeněk {Dufek} and Joanna {Ejdys} and Romualdas {Ginevičius} and Pawel {Korzynski} and Grzegorz {Mazurek} and Joanna {Paliszkiewicz} and Krzysztof {Wach} and Ewa {Ziemba}",
  title="Generative AI in the manufacturing process: theoretical considerations",
  journal="Engineering Management in Production and Services",
  year="2023",
  volume="15",
  number="4",
  pages="76--89",
  doi="10.2478/emj-2023-0029",
  issn="2543-6597",
  url="https://sciendo.com/article/10.2478/emj-2023-0029"
}