Generative AI in the Manufacturing Process: Theoretical Considerations

Doanh Doung Cong, Dufek Zdenek, Ejdys Joanna (), Ginevičius Romualdas, Korzynski Pawel, Mazurek Grzegorz, Paliszkiewicz Joanna, Wach Krzysztof and Ziemba Ewa
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Doanh Doung Cong: National Economics University, Hanoi, Vietnam
Dufek Zdenek: Brno University of Technology, Czechia
Ejdys Joanna: Bialystok University of Technology, Poland
Ginevičius Romualdas: Mykolas Romeris University, Lithuania
Korzynski Pawel: Kozminski University, Poland
Mazurek Grzegorz: Kozminski University, Poland
Paliszkiewicz Joanna: Warsaw University of Life Sciences, Poland
Wach Krzysztof: Krakow University of Economics, Poland
Ziemba Ewa: University of Economics in Katowice, Poland

Engineering Management in Production and Services, 2023, vol. 15, issue 4, 76-89

Abstract: 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.

Keywords: Generative AI; ChatGPT; Industry 4.0; technology; manufacturing processes (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:ecoman:v:15:y:2023:i:4:p:76-89:n:3

DOI: 10.2478/emj-2023-0029

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