Szczegóły publikacji
Opis bibliograficzny
Application of AI and VR in production management / Katarzyna ŁYP-WROŃSKA, Maciej JAMIŃSKI // Scientific Papers of Silesian University of Technology [Dokument elektroniczny]. — Czasopismo elektroniczne ; ISSN 2720-751X. Organization & Management ; ISSN 2720-751X. — 2025 — no. 231, s. 289-315. — Wymagania systemowe: Adobe Reader. — Bibliogr. s. 311-315, Abstr.
Autorzy (2)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 164190 |
|---|---|
| Data dodania do BaDAP | 2025-11-18 |
| Tekst źródłowy | URL |
| DOI | 10.29119/1641-3466.2025.231.18 |
| Rok publikacji | 2025 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Creative Commons | |
| Czasopismo/seria | Zeszyty Naukowe Politechniki Śląskiej = Scientific Journal of Silesian University of Technology, Organizacja i Zarządzanie = Organization & Management |
Abstract
Purpose: This paper investigates the use of Artificial Intelligence (AI) and Virtual Reality (VR) in production management. The goal is to identify research trends, integration models with MES/ERP systems, and key challenges associated with the implementation of these technologies in industrial practice, particularly in the context of Industry 4.0 and 5.0. Design/methodology/approach: The research combines a Systematic Literature Review (SLR) with bibliometric analysis based on Scopus data up to May 1, 2025. The SLR focuses on peer-reviewed publications related to AI and VR in production. Bibliometric analysis includes publication dynamics, geographic distribution, institutional affiliations, authorship, and subject area classifications. Findings: A marked increase in publication output has been observed since 2016, with a peak in 2023. AI and VR are increasingly used in production layout design, predictive maintenance, risk management, training, and system integration. Engineering and Computer Science dominate the field. China, the USA, and India lead in publication volume. However, few studies focus on integrated AI–VR systems or real-world implementations. Research limitations/implications: The study is limited to English-language publications indexed in Scopus and focused solely on production (excluding quality management). Future research should address real-case studies, ROI/KPI evaluation, and organizational challenges in AI/VR adoption. Practical implications: Results support industrial decision-makers in selecting, integrating, and scaling AI/VR tools. Emphasis is placed on improving interoperability, process flexibility, and workforce training within digital production systems. Social implications: The research highlights how immersive and intelligent technologies can enhance safety, competence, and human-centered design in production, contributing to sustainable development and smart work environments. Value: This is the first study to provide a focused, bibliometric SLR on AI and VR applications in production management. It offers a structured synthesis useful for scholars, practitioners, and policy designers seeking to align digital transformation with operational needs.
