AI-Driven Manufacturing: Surveying for Industry 4.0 and Beyond

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F25%3A00385731" target="_blank" >RIV/68407700:21230/25:00385731 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1007/s43069-025-00554-6" target="_blank" >https://doi.org/10.1007/s43069-025-00554-6</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s43069-025-00554-6" target="_blank" >10.1007/s43069-025-00554-6</a>

Jazyk výsledku

angličtina

Název v původním jazyce

AI-Driven Manufacturing: Surveying for Industry 4.0 and Beyond

Popis výsledku v původním jazyce

Artificial intelligence is transforming various industries, including manufacturing, yet its full potential in manufacturing remains underutilized. Industry 4.0 aims to enhance productivity, operational efficiency, and decision-making, but achieving these objectives at scale remains an ongoing challenge. This paper surveys the artificial intelligence-driven integration of multi-agent systems and manufacturing execution systems as key enablers of smart manufacturing in Industry 4.0 and the emerging Industry 5.0. It reviews state-of-the-art developments, identifies key challenges, and outlines research priorities by analyzing trends from past industrial revolutions. The paper also emphasizes workforce upskilling and advocates for a problem-driven approach, prioritizing solving practical challenges over pursuing technological innovation without clear objectives. Furthermore, this paper leverages responses generated via ChatGPT and Microsoft Copilot to assess whether the discussions presented align with AI-generated insights, demonstrating an example of human–machine collaboration to set a precedent for future research. Concluding with a forward-looking agenda, it emphasizes the need for high-technology readiness level pilot implementations and stronger industry-academia collaboration to transition from theoretical breakthroughs to large-scale industrial deployment. This paper serves as a guide for researchers, policymakers, and stakeholders, providing a comprehensive perspective on technological advancements, integration challenges, and industry standards in smart manufacturing.

Název v anglickém jazyce

AI-Driven Manufacturing: Surveying for Industry 4.0 and Beyond

Popis výsledku anglicky

Artificial intelligence is transforming various industries, including manufacturing, yet its full potential in manufacturing remains underutilized. Industry 4.0 aims to enhance productivity, operational efficiency, and decision-making, but achieving these objectives at scale remains an ongoing challenge. This paper surveys the artificial intelligence-driven integration of multi-agent systems and manufacturing execution systems as key enablers of smart manufacturing in Industry 4.0 and the emerging Industry 5.0. It reviews state-of-the-art developments, identifies key challenges, and outlines research priorities by analyzing trends from past industrial revolutions. The paper also emphasizes workforce upskilling and advocates for a problem-driven approach, prioritizing solving practical challenges over pursuing technological innovation without clear objectives. Furthermore, this paper leverages responses generated via ChatGPT and Microsoft Copilot to assess whether the discussions presented align with AI-generated insights, demonstrating an example of human–machine collaboration to set a precedent for future research. Concluding with a forward-looking agenda, it emphasizes the need for high-technology readiness level pilot implementations and stronger industry-academia collaboration to transition from theoretical breakthroughs to large-scale industrial deployment. This paper serves as a guide for researchers, policymakers, and stakeholders, providing a comprehensive perspective on technological advancements, integration challenges, and industry standards in smart manufacturing.

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/EH22_008%2F0004590" target="_blank" >EH22_008/0004590: Robotika a pokročilá průmyslová výroba</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2025

Kód důvěrnosti údajů

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

Název periodika

Operations Research Forum

ISSN

2662-2556

e-ISSN

2662-2556

Svazek periodika

6

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

31

Strana od-do

—

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-105017153492