Generative AI in the manufacturing process: theoretical considerations

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26110%2F23%3APU150098" target="_blank" >RIV/00216305:26110/23:PU150098 - isvavai.cz</a>

Výsledek na webu

<a href="https://sciendo.com/article/10.2478/emj-2023-0029" target="_blank" >https://sciendo.com/article/10.2478/emj-2023-0029</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.2478/emj-2023-0029" target="_blank" >10.2478/emj-2023-0029</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Generative AI in the manufacturing process: theoretical considerations

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Generative AI in the manufacturing process: theoretical considerations

Popis výsledku anglicky

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.

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

—

OECD FORD obor

20101 - Civil engineering

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Engineering Management in Production and Services

ISSN

2543-6597

e-ISSN

—

Svazek periodika

15

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

PL - Polská republika

Počet stran výsledku

14

Strana od-do

76-89

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-85182436211